R/05-recode_anc.R
In validmeasures/myanmarMCCTdata: Myanmar Mother and Child Cash Transfer (MCCT) Programme Evaluation Data Handler
Defines functions
create_anc
recode_provider_specialist
recode_provider_doctor
recode_provider_nurse
recode_provider_ha
recode_provider_pdoc
recode_provider_lhv
recode_provider_midwife
recode_provider_amw
recode_provider_tba
recode_provider_chw
recode_provider_ehw
recode_anc_provider
recode_anc_counselling
recode_anc_supplementation
recode_anc_testing
recode_anc
Documented in
create_anc
recode_anc
recode_anc_counselling
recode_anc_provider
recode_anc_supplementation
recode_anc_testing
recode_provider_amw
recode_provider_chw
recode_provider_doctor
recode_provider_ehw
recode_provider_ha
recode_provider_lhv
recode_provider_midwife
recode_provider_nurse
recode_provider_pdoc
recode_provider_specialist
recode_provider_tba
################################################################################
#
#' Function to create raw ANC dataset
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing ANC data
#' @param x A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing household information that will be linked to the
#' ANC data
#' @param y A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing household roster information that will be linked to the
#' ANC data
#' @param status A character value indicating whether to create data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame containing raw ANC data for the Myanmar MCCT Programme
#' Evaluation Study
#'
#' @examples
#' create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#'
#' @export
#'
#
################################################################################
create_anc <- function(df, x, y, status) {
## Create data.frame from hh dataset to get needed information
x <- x[ , c("KEY", "intrv_date", "geo_state", "geo_rural", "geo_villward",
"sample_component", "will_participate")]
## Create data.frame from hhMembers dataset to get needed information
y <- y[ , c("PARENT_KEY", "KEY", "hh_mem_sex", "hh_mem_age",
"hh_mem_age_month", "hh_mem_dob", "hh_mem_pregnow",
"hh_mem_u5num", "hh_mem_highedu", "hh_mem_occup")]
if(status == "current") {
## change KEY to match anc1 KEY
y$KEY <- stringr::str_replace_all(string = y$KEY,
pattern = "grp_hh",
replacement = "ancnow_rep")
}
if(status == "past") {
## change KEY to match anc2 KEY
y$KEY <- stringr::str_replace_all(string = y$KEY,
pattern = "grp_hh",
replacement = "ancpast_rep")
}
## Merge hhMembers data with childHealth to get hhMember information
xy <- merge(y, df, by.x = "KEY", by.y = "KEY", all.y = TRUE)
## Merge hh data with merged childHealth data to get hh information
z <- merge(x, xy, by.x = "KEY", by.y = "PARENT_KEY.y", all.y = TRUE)
## Calculate age in days
age <- floor(as.numeric(lubridate::mdy(z$intrv_date) -
lubridate::mdy(z$hh_mem_dob)) / 365.25)
age <- ifelse(is.na(age),
floor(sum(as.integer(z$hh_mem_age),
(as.integer(z$hh_mem_age_month) / 12),
na.rm = TRUE)),
age)
## Add age to data.frame
z$age <- age
if(status == "current") {
z <- z[as.integer(z$hh_mem_pregnow) == 1 & !is.na(z$hh_mem_pregnow), ]
}
if(status == "past") {
z <- z[as.integer(z$hh_mem_pregnow) == 0 &
!is.na(z$hh_mem_pregnow) &
as.integer(z$hh_mem_u5num) > 0 & !is.na(z$hh_mem_u5num), ]
}
## remove unnecessary variables
z <- z[ , names(z)[!names(z) %in% c("KEY.y",
"PARENT_KEY.x",
"SET.OF.ancnow_rep",
"SET.OF.ancpast_rep")]]
## return data.frame
return(z)
}
################################################################################
#
#' Function to recode the specialist ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded specialist ANC provider information
#'
#' @examples
#' ## Recode specialist provider for current pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_specialist(df = x, status = "current")
#'
#' ## Recode specialist provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_specialist(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_specialist <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend specialist
specialist <- as.integer(df$ancnow_who.1)
## Where specialist
specialist.where <- as.integer(df$ancnow_pdoc_where)
specialist.home <- bbw::recode(var = specialist.where,
recodes = "1=1;NA=NA;else=0")
specialist.gov <- bbw::recode(var = specialist.where,
recodes = "2=1;NA=NA;else=0")
specialist.private <- bbw::recode(var = specialist.where,
recodes = "3=1;NA=NA;else=0")
specialist.srhc <- bbw::recode(var = specialist.where,
recodes = "4=1;NA=NA;else=0")
specialist.village <- bbw::recode(var = specialist.where,
recodes = "5=1;NA=NA;else=0")
specialist.eho <- bbw::recode(var = specialist.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
specialist.dry <- as.integer(df$ancnow_pdoc_dist_dry)
specialist.dry.lt15 <- bbw::recode(var = specialist.dry,
recodes = "1=1;NA=NA;else=0")
specialist.dry.gteq15lt60 <- bbw::recode(var = specialist.dry,
recodes = "2=1;NA=NA;else=0")
specialist.dry.gteq60lt120 <- bbw::recode(var = specialist.dry,
recodes = "3=1;NA=NA;else=0")
specialist.dry.gteq120lt360 <- bbw::recode(var = specialist.dry,
recodes = "4=1;NA=NA;else=0")
specialist.dry.gteq360lt720 <- bbw::recode(var = specialist.dry,
recodes = "5=1;NA=NA;else=0")
specialist.dry.gteq720lt1440 <- bbw::recode(var = specialist.dry,
recodes = "6=1;NA=NA;else=0")
specialist.dry.gteq1440 <- bbw::recode(var = specialist.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
specialist.wet <- as.integer(df$ancnow_pdoc_dist_wet)
specialist.wet.lt15 <- bbw::recode(var = specialist.wet,
recodes = "1=1;NA=NA;else=0")
specialist.wet.gteq15lt60 <- bbw::recode(var = specialist.wet,
recodes = "2=1;NA=NA;else=0")
specialist.wet.gteq60lt120 <- bbw::recode(var = specialist.wet,
recodes = "3=1;NA=NA;else=0")
specialist.wet.gteq120lt360 <- bbw::recode(var = specialist.wet,
recodes = "4=1;NA=NA;else=0")
specialist.wet.gteq360lt720 <- bbw::recode(var = specialist.wet,
recodes = "5=1;NA=NA;else=0")
specialist.wet.gteq720lt1440 <- bbw::recode(var = specialist.wet,
recodes = "6=1;NA=NA;else=0")
specialist.wet.gteq1440 <- bbw::recode(var = specialist.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
specialist.visit <- as.integer(df$ancnow_pdoc_visit)
## Number of visits per trimester
specialist.visit.first <- as.integer(df$ancnow_pdoc_1tri_times)
specialist.visit.second <- as.integer(df$ancnow_pdoc_2tri_times)
specialist.visit.third <- as.integer(df$ancnow_pdoc_3tri_times)
## Concatenate specialist provider data.frame
specialist <- data.frame(specialist, specialist.where, specialist.home,
specialist.gov, specialist.private, specialist.srhc,
specialist.village, specialist.eho, specialist.dry,
specialist.dry.lt15, specialist.dry.gteq15lt60,
specialist.dry.gteq60lt120,
specialist.dry.gteq120lt360,
specialist.dry.gteq360lt720,
specialist.dry.gteq720lt1440,
specialist.dry.gteq1440, specialist.wet,
specialist.wet.lt15, specialist.wet.gteq15lt60,
specialist.wet.gteq60lt120,
specialist.wet.gteq120lt360,
specialist.wet.gteq360lt720,
specialist.wet.gteq720lt1440,
specialist.wet.gteq1440, specialist.visit,
specialist.visit.first, specialist.visit.second,
specialist.visit.third)
} else {
## Attend specialist
specialist <- as.integer(df$ancpast_who.1)
## Where specialist
specialist.where <- as.integer(df$ancpast_pdoc_where)
specialist.home <- bbw::recode(var = specialist.where,
recodes = "1=1;NA=NA;else=0")
specialist.gov <- bbw::recode(var = specialist.where,
recodes = "2=1;NA=NA;else=0")
specialist.private <- bbw::recode(var = specialist.where,
recodes = "3=1;NA=NA;else=0")
specialist.srhc <- bbw::recode(var = specialist.where,
recodes = "4=1;NA=NA;else=0")
specialist.village <- bbw::recode(var = specialist.where,
recodes = "5=1;NA=NA;else=0")
specialist.eho <- bbw::recode(var = specialist.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
specialist.dry <- as.integer(df$ancpast_pdoc_dist_dry)
specialist.dry.lt15 <- bbw::recode(var = specialist.dry,
recodes = "1=1;NA=NA;else=0")
specialist.dry.gteq15lt60 <- bbw::recode(var = specialist.dry,
recodes = "2=1;NA=NA;else=0")
specialist.dry.gteq60lt120 <- bbw::recode(var = specialist.dry,
recodes = "3=1;NA=NA;else=0")
specialist.dry.gteq120lt360 <- bbw::recode(var = specialist.dry,
recodes = "4=1;NA=NA;else=0")
specialist.dry.gteq360lt720 <- bbw::recode(var = specialist.dry,
recodes = "5=1;NA=NA;else=0")
specialist.dry.gteq720lt1440 <- bbw::recode(var = specialist.dry,
recodes = "6=1;NA=NA;else=0")
specialist.dry.gteq1440 <- bbw::recode(var = specialist.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
specialist.wet <- as.integer(df$ancpast_pdoc_dist_wet)
specialist.wet.lt15 <- bbw::recode(var = specialist.wet,
recodes = "1=1;NA=NA;else=0")
specialist.wet.gteq15lt60 <- bbw::recode(var = specialist.wet,
recodes = "2=1;NA=NA;else=0")
specialist.wet.gteq60lt120 <- bbw::recode(var = specialist.wet,
recodes = "3=1;NA=NA;else=0")
specialist.wet.gteq120lt360 <- bbw::recode(var = specialist.wet,
recodes = "4=1;NA=NA;else=0")
specialist.wet.gteq360lt720 <- bbw::recode(var = specialist.wet,
recodes = "5=1;NA=NA;else=0")
specialist.wet.gteq720lt1440 <- bbw::recode(var = specialist.wet,
recodes = "6=1;NA=NA;else=0")
specialist.wet.gteq1440 <- bbw::recode(var = specialist.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
specialist.visit <- as.integer(df$ancpast_pdoc_visit)
## Number of visits per trimester
specialist.visit.first <- as.integer(df$ancpast_pdoc_1tri_times)
specialist.visit.second <- as.integer(df$ancpast_pdoc_2tri_times)
specialist.visit.third <- as.integer(df$ancpast_pdoc_3tri_times)
## Concatenate specialist provider data.frame
specialist <- data.frame(specialist, specialist.where, specialist.home,
specialist.gov,
specialist.private, specialist.srhc,
specialist.village,
specialist.eho, specialist.dry,
specialist.dry.lt15, specialist.dry.gteq15lt60,
specialist.dry.gteq60lt120,
specialist.dry.gteq120lt360,
specialist.dry.gteq360lt720,
specialist.dry.gteq720lt1440,
specialist.dry.gteq1440, specialist.wet,
specialist.wet.lt15, specialist.wet.gteq15lt60,
specialist.wet.gteq60lt120,
specialist.wet.gteq120lt360,
specialist.wet.gteq360lt720,
specialist.wet.gteq720lt1440,
specialist.wet.gteq1440, specialist.visit,
specialist.visit.first, specialist.visit.second,
specialist.visit.third)
}
## Return data.frame
return(specialist)
}
################################################################################
#
#' Function to recode the doctor ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded doctor ANC provider information
#'
#' @examples
#' ## Recode provider doctor for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_doctor(df = x, status = "current")
#'
#' ## Recode provider doctor for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_doctor(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_doctor <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend doctor
doctor <- as.integer(df$ancnow_who.2)
## Where doctor
doctor.where <- as.integer(df$ancnow_doc_where)
doctor.home <- bbw::recode(var = doctor.where,
recodes = "1=1;NA=NA;else=0")
doctor.gov <- bbw::recode(var = doctor.where,
recodes = "2=1;NA=NA;else=0")
doctor.private <- bbw::recode(var = doctor.where,
recodes = "3=1;NA=NA;else=0")
doctor.srhc <- bbw::recode(var = doctor.where,
recodes = "4=1;NA=NA;else=0")
doctor.village <- bbw::recode(var = doctor.where,
recodes = "5=1;NA=NA;else=0")
doctor.eho <- bbw::recode(var = doctor.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
doctor.dry <- as.integer(df$ancnow_doc_dist_dry)
doctor.dry.lt15 <- bbw::recode(var = doctor.dry,
recodes = "1=1;NA=NA;else=0")
doctor.dry.gteq15lt60 <- bbw::recode(var = doctor.dry,
recodes = "2=1;NA=NA;else=0")
doctor.dry.gteq60lt120 <- bbw::recode(var = doctor.dry,
recodes = "3=1;NA=NA;else=0")
doctor.dry.gteq120lt360 <- bbw::recode(var = doctor.dry,
recodes = "4=1;NA=NA;else=0")
doctor.dry.gteq360lt720 <- bbw::recode(var = doctor.dry,
recodes = "5=1;NA=NA;else=0")
doctor.dry.gteq720lt1440 <- bbw::recode(var = doctor.dry,
recodes = "6=1;NA=NA;else=0")
doctor.dry.gteq1440 <- bbw::recode(var = doctor.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
doctor.wet <- as.integer(df$ancnow_doc_dist_wet)
doctor.wet.lt15 <- bbw::recode(var = doctor.wet,
recodes = "1=1;NA=NA;else=0")
doctor.wet.gteq15lt60 <- bbw::recode(var = doctor.wet,
recodes = "2=1;NA=NA;else=0")
doctor.wet.gteq60lt120 <- bbw::recode(var = doctor.wet,
recodes = "3=1;NA=NA;else=0")
doctor.wet.gteq120lt360 <- bbw::recode(var = doctor.wet,
recodes = "4=1;NA=NA;else=0")
doctor.wet.gteq360lt720 <- bbw::recode(var = doctor.wet,
recodes = "5=1;NA=NA;else=0")
doctor.wet.gteq720lt1440 <- bbw::recode(var = doctor.wet,
recodes = "6=1;NA=NA;else=0")
doctor.wet.gteq1440 <- bbw::recode(var = doctor.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
doctor.visit <- as.integer(df$ancnow_doc_visit)
## Number of visits per trimester
doctor.visit.first <- as.integer(df$ancnow_doc_1tri_times)
doctor.visit.second <- as.integer(df$ancnow_doc_2tri_times)
doctor.visit.third <- as.integer(df$ancnow_doc_3tri_times)
## Concatenate doctor provider data.frame
doctor <- data.frame(doctor, doctor.where, doctor.home,
doctor.gov, doctor.private, doctor.srhc,
doctor.village, doctor.eho, doctor.dry,
doctor.dry.lt15, doctor.dry.gteq15lt60,
doctor.dry.gteq60lt120, doctor.dry.gteq120lt360,
doctor.dry.gteq360lt720, doctor.dry.gteq720lt1440,
doctor.dry.gteq1440, doctor.wet,
doctor.wet.lt15, doctor.wet.gteq15lt60,
doctor.wet.gteq60lt120, doctor.wet.gteq120lt360,
doctor.wet.gteq360lt720, doctor.wet.gteq720lt1440,
doctor.wet.gteq1440, doctor.visit,
doctor.visit.first, doctor.visit.second,
doctor.visit.third)
} else {
## Attend doctor
doctor <- as.integer(df$ancpast_who.2)
## Where doctor
doctor.where <- as.integer(df$ancpast_doc_where)
doctor.home <- bbw::recode(var = doctor.where,
recodes = "1=1;NA=NA;else=0")
doctor.gov <- bbw::recode(var = doctor.where,
recodes = "2=1;NA=NA;else=0")
doctor.private <- bbw::recode(var = doctor.where,
recodes = "3=1;NA=NA;else=0")
doctor.srhc <- bbw::recode(var = doctor.where,
recodes = "4=1;NA=NA;else=0")
doctor.village <- bbw::recode(var = doctor.where,
recodes = "5=1;NA=NA;else=0")
doctor.eho <- bbw::recode(var = doctor.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
doctor.dry <- as.integer(df$ancpast_doc_dist_dry)
doctor.dry.lt15 <- bbw::recode(var = doctor.dry,
recodes = "1=1;NA=NA;else=0")
doctor.dry.gteq15lt60 <- bbw::recode(var = doctor.dry,
recodes = "2=1;NA=NA;else=0")
doctor.dry.gteq60lt120 <- bbw::recode(var = doctor.dry,
recodes = "3=1;NA=NA;else=0")
doctor.dry.gteq120lt360 <- bbw::recode(var = doctor.dry,
recodes = "4=1;NA=NA;else=0")
doctor.dry.gteq360lt720 <- bbw::recode(var = doctor.dry,
recodes = "5=1;NA=NA;else=0")
doctor.dry.gteq720lt1440 <- bbw::recode(var = doctor.dry,
recodes = "6=1;NA=NA;else=0")
doctor.dry.gteq1440 <- bbw::recode(var = doctor.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
doctor.wet <- as.integer(df$ancpast_doc_dist_wet)
doctor.wet.lt15 <- bbw::recode(var = doctor.wet,
recodes = "1=1;NA=NA;else=0")
doctor.wet.gteq15lt60 <- bbw::recode(var = doctor.wet,
recodes = "2=1;NA=NA;else=0")
doctor.wet.gteq60lt120 <- bbw::recode(var = doctor.wet,
recodes = "3=1;NA=NA;else=0")
doctor.wet.gteq120lt360 <- bbw::recode(var = doctor.wet,
recodes = "4=1;NA=NA;else=0")
doctor.wet.gteq360lt720 <- bbw::recode(var = doctor.wet,
recodes = "5=1;NA=NA;else=0")
doctor.wet.gteq720lt1440 <- bbw::recode(var = doctor.wet,
recodes = "6=1;NA=NA;else=0")
doctor.wet.gteq1440 <- bbw::recode(var = doctor.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
doctor.visit <- as.integer(df$ancpast_doc_visit)
## Number of visits per trimester
doctor.visit.first <- as.integer(df$ancpast_doc_1tri_times)
doctor.visit.second <- as.integer(df$ancpast_doc_2tri_times)
doctor.visit.third <- as.integer(df$ancpast_doc_3tri_times)
## Concatenate doctor provider data.frame
doctor <- data.frame(doctor, doctor.where, doctor.home,
doctor.gov, doctor.private, doctor.srhc,
doctor.village, doctor.eho, doctor.dry,
doctor.dry.lt15, doctor.dry.gteq15lt60,
doctor.dry.gteq60lt120, doctor.dry.gteq120lt360,
doctor.dry.gteq360lt720, doctor.dry.gteq720lt1440,
doctor.dry.gteq1440, doctor.wet,
doctor.wet.lt15, doctor.wet.gteq15lt60,
doctor.wet.gteq60lt120, doctor.wet.gteq120lt360,
doctor.wet.gteq360lt720, doctor.wet.gteq720lt1440,
doctor.wet.gteq1440, doctor.visit,
doctor.visit.first, doctor.visit.second,
doctor.visit.third)
}
## Return data.frame
return(doctor)
}
################################################################################
#
#' Function to recode the nurse ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded nurse ANC provider information
#'
#' @examples
#' ## Recode nurse provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_nurse(df = x, status = "current")
#'
#' ## Recode nurse provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_nurse(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_nurse <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend nurse
nurse <- as.integer(df$ancnow_who.3)
## Where nurse
nurse.where <- as.integer(df$ancnow_nurs_where)
nurse.home <- bbw::recode(var = nurse.where,
recodes = "1=1;NA=NA;else=0")
nurse.gov <- bbw::recode(var = nurse.where,
recodes = "2=1;NA=NA;else=0")
nurse.private <- bbw::recode(var = nurse.where,
recodes = "3=1;NA=NA;else=0")
nurse.srhc <- bbw::recode(var = nurse.where,
recodes = "4=1;NA=NA;else=0")
nurse.village <- bbw::recode(var = nurse.where,
recodes = "5=1;NA=NA;else=0")
nurse.eho <- bbw::recode(var = nurse.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
nurse.dry <- as.integer(df$ancnow_nurs_dist_dry)
nurse.dry.lt15 <- bbw::recode(var = nurse.dry,
recodes = "1=1;NA=NA;else=0")
nurse.dry.gteq15lt60 <- bbw::recode(var = nurse.dry,
recodes = "2=1;NA=NA;else=0")
nurse.dry.gteq60lt120 <- bbw::recode(var = nurse.dry,
recodes = "3=1;NA=NA;else=0")
nurse.dry.gteq120lt360 <- bbw::recode(var = nurse.dry,
recodes = "4=1;NA=NA;else=0")
nurse.dry.gteq360lt720 <- bbw::recode(var = nurse.dry,
recodes = "5=1;NA=NA;else=0")
nurse.dry.gteq720lt1440 <- bbw::recode(var = nurse.dry,
recodes = "6=1;NA=NA;else=0")
nurse.dry.gteq1440 <- bbw::recode(var = nurse.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
nurse.wet <- as.integer(df$ancnow_nurs_dist_wet)
nurse.wet.lt15 <- bbw::recode(var = nurse.wet,
recodes = "1=1;NA=NA;else=0")
nurse.wet.gteq15lt60 <- bbw::recode(var = nurse.wet,
recodes = "2=1;NA=NA;else=0")
nurse.wet.gteq60lt120 <- bbw::recode(var = nurse.wet,
recodes = "3=1;NA=NA;else=0")
nurse.wet.gteq120lt360 <- bbw::recode(var = nurse.wet,
recodes = "4=1;NA=NA;else=0")
nurse.wet.gteq360lt720 <- bbw::recode(var = nurse.wet,
recodes = "5=1;NA=NA;else=0")
nurse.wet.gteq720lt1440 <- bbw::recode(var = nurse.wet,
recodes = "6=1;NA=NA;else=0")
nurse.wet.gteq1440 <- bbw::recode(var = nurse.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
nurse.visit <- as.integer(df$ancnow_nurs_visit)
## Number of visits per trimester
nurse.visit.first <- as.integer(df$ancnow_nurs_1tri_times)
nurse.visit.second <- as.integer(df$ancnow_nurs_2tri_times)
nurse.visit.third <- as.integer(df$ancnow_nurs_3tri_times)
## Concatenate nurse provider data.frame
nurse <- data.frame(nurse, nurse.where, nurse.home,
nurse.gov, nurse.private, nurse.srhc,
nurse.village, nurse.eho, nurse.dry,
nurse.dry.lt15, nurse.dry.gteq15lt60,
nurse.dry.gteq60lt120, nurse.dry.gteq120lt360,
nurse.dry.gteq360lt720, nurse.dry.gteq720lt1440,
nurse.dry.gteq1440, nurse.wet,
nurse.wet.lt15, nurse.wet.gteq15lt60,
nurse.wet.gteq60lt120, nurse.wet.gteq120lt360,
nurse.wet.gteq360lt720, nurse.wet.gteq720lt1440,
nurse.wet.gteq1440, nurse.visit,
nurse.visit.first, nurse.visit.second,
nurse.visit.third)
} else {
## Attend nurse
nurse <- as.integer(df$ancpast_who.3)
## Where nurse
nurse.where <- as.integer(df$ancpast_nurs_where)
nurse.home <- bbw::recode(var = nurse.where,
recodes = "1=1;NA=NA;else=0")
nurse.gov <- bbw::recode(var = nurse.where,
recodes = "2=1;NA=NA;else=0")
nurse.private <- bbw::recode(var = nurse.where,
recodes = "3=1;NA=NA;else=0")
nurse.srhc <- bbw::recode(var = nurse.where,
recodes = "4=1;NA=NA;else=0")
nurse.village <- bbw::recode(var = nurse.where,
recodes = "5=1;NA=NA;else=0")
nurse.eho <- bbw::recode(var = nurse.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
nurse.dry <- as.integer(df$ancpast_nurs_dist_dry)
nurse.dry.lt15 <- bbw::recode(var = nurse.dry,
recodes = "1=1;NA=NA;else=0")
nurse.dry.gteq15lt60 <- bbw::recode(var = nurse.dry,
recodes = "2=1;NA=NA;else=0")
nurse.dry.gteq60lt120 <- bbw::recode(var = nurse.dry,
recodes = "3=1;NA=NA;else=0")
nurse.dry.gteq120lt360 <- bbw::recode(var = nurse.dry,
recodes = "4=1;NA=NA;else=0")
nurse.dry.gteq360lt720 <- bbw::recode(var = nurse.dry,
recodes = "5=1;NA=NA;else=0")
nurse.dry.gteq720lt1440 <- bbw::recode(var = nurse.dry,
recodes = "6=1;NA=NA;else=0")
nurse.dry.gteq1440 <- bbw::recode(var = nurse.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
nurse.wet <- as.integer(df$ancpast_nurs_dist_wet)
nurse.wet.lt15 <- bbw::recode(var = nurse.wet,
recodes = "1=1;NA=NA;else=0")
nurse.wet.gteq15lt60 <- bbw::recode(var = nurse.wet,
recodes = "2=1;NA=NA;else=0")
nurse.wet.gteq60lt120 <- bbw::recode(var = nurse.wet,
recodes = "3=1;NA=NA;else=0")
nurse.wet.gteq120lt360 <- bbw::recode(var = nurse.wet,
recodes = "4=1;NA=NA;else=0")
nurse.wet.gteq360lt720 <- bbw::recode(var = nurse.wet,
recodes = "5=1;NA=NA;else=0")
nurse.wet.gteq720lt1440 <- bbw::recode(var = nurse.wet,
recodes = "6=1;NA=NA;else=0")
nurse.wet.gteq1440 <- bbw::recode(var = nurse.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
nurse.visit <- as.integer(df$ancpast_nurs_visit)
## Number of visits per trimester
nurse.visit.first <- as.integer(df$ancpast_nurs_1tri_times)
nurse.visit.second <- as.integer(df$ancpast_nurs_2tri_times)
nurse.visit.third <- as.integer(df$ancpast_nurs_3tri_times)
## Concatenate nurse provider data.frame
nurse <- data.frame(nurse, nurse.where, nurse.home,
nurse.gov, nurse.private, nurse.srhc,
nurse.village, nurse.eho, nurse.dry,
nurse.dry.lt15, nurse.dry.gteq15lt60,
nurse.dry.gteq60lt120, nurse.dry.gteq120lt360,
nurse.dry.gteq360lt720, nurse.dry.gteq720lt1440,
nurse.dry.gteq1440, nurse.wet,
nurse.wet.lt15, nurse.wet.gteq15lt60,
nurse.wet.gteq60lt120, nurse.wet.gteq120lt360,
nurse.wet.gteq360lt720, nurse.wet.gteq720lt1440,
nurse.wet.gteq1440, nurse.visit,
nurse.visit.first, nurse.visit.second,
nurse.visit.third)
}
## Return data.frame
return(nurse)
}
################################################################################
#
#' Function to recode the health assistant ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded health assistant ANC provider information
#'
#' @examples
#' ## Recode health assistant provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_ha(df = x, status = "current")
#'
#' ## Recode health assistant provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_ha(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_ha <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend ha
ha <- as.integer(df$ancnow_who.4)
## Where ha
ha.where <- as.integer(df$ancnow_ha_where)
ha.home <- bbw::recode(var = ha.where,
recodes = "1=1;NA=NA;else=0")
ha.gov <- bbw::recode(var = ha.where,
recodes = "2=1;NA=NA;else=0")
ha.private <- bbw::recode(var = ha.where,
recodes = "3=1;NA=NA;else=0")
ha.srhc <- bbw::recode(var = ha.where,
recodes = "4=1;NA=NA;else=0")
ha.village <- bbw::recode(var = ha.where,
recodes = "5=1;NA=NA;else=0")
ha.eho <- bbw::recode(var = ha.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ha.dry <- as.integer(df$ancnow_ha_dist_dry)
ha.dry.lt15 <- bbw::recode(var = ha.dry,
recodes = "1=1;NA=NA;else=0")
ha.dry.gteq15lt60 <- bbw::recode(var = ha.dry,
recodes = "2=1;NA=NA;else=0")
ha.dry.gteq60lt120 <- bbw::recode(var = ha.dry,
recodes = "3=1;NA=NA;else=0")
ha.dry.gteq120lt360 <- bbw::recode(var = ha.dry,
recodes = "4=1;NA=NA;else=0")
ha.dry.gteq360lt720 <- bbw::recode(var = ha.dry,
recodes = "5=1;NA=NA;else=0")
ha.dry.gteq720lt1440 <- bbw::recode(var = ha.dry,
recodes = "6=1;NA=NA;else=0")
ha.dry.gteq1440 <- bbw::recode(var = ha.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ha.wet <- as.integer(df$ancnow_ha_dist_wet)
ha.wet.lt15 <- bbw::recode(var = ha.wet,
recodes = "1=1;NA=NA;else=0")
ha.wet.gteq15lt60 <- bbw::recode(var = ha.wet,
recodes = "2=1;NA=NA;else=0")
ha.wet.gteq60lt120 <- bbw::recode(var = ha.wet,
recodes = "3=1;NA=NA;else=0")
ha.wet.gteq120lt360 <- bbw::recode(var = ha.wet,
recodes = "4=1;NA=NA;else=0")
ha.wet.gteq360lt720 <- bbw::recode(var = ha.wet,
recodes = "5=1;NA=NA;else=0")
ha.wet.gteq720lt1440 <- bbw::recode(var = ha.wet,
recodes = "6=1;NA=NA;else=0")
ha.wet.gteq1440 <- bbw::recode(var = ha.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ha.visit <- as.integer(df$ancnow_ha_visit)
## Number of visits per trimester
ha.visit.first <- as.integer(df$ancnow_ha_1tri_times)
ha.visit.second <- as.integer(df$ancnow_ha_2tri_times)
ha.visit.third <- as.integer(df$ancnow_ha_3tri_times)
## Concatenate ha provider data.frame
ha <- data.frame(ha, ha.where, ha.home,
ha.gov, ha.private, ha.srhc,
ha.village, ha.eho, ha.dry,
ha.dry.lt15, ha.dry.gteq15lt60,
ha.dry.gteq60lt120, ha.dry.gteq120lt360,
ha.dry.gteq360lt720, ha.dry.gteq720lt1440,
ha.dry.gteq1440, ha.wet,
ha.wet.lt15, ha.wet.gteq15lt60,
ha.wet.gteq60lt120, ha.wet.gteq120lt360,
ha.wet.gteq360lt720, ha.wet.gteq720lt1440,
ha.wet.gteq1440, ha.visit,
ha.visit.first, ha.visit.second,
ha.visit.third)
} else {
## Attend ha
ha <- as.integer(df$ancpast_who.4)
## Where ha
ha.where <- as.integer(df$ancpast_ha_where)
ha.home <- bbw::recode(var = ha.where,
recodes = "1=1;NA=NA;else=0")
ha.gov <- bbw::recode(var = ha.where,
recodes = "2=1;NA=NA;else=0")
ha.private <- bbw::recode(var = ha.where,
recodes = "3=1;NA=NA;else=0")
ha.srhc <- bbw::recode(var = ha.where,
recodes = "4=1;NA=NA;else=0")
ha.village <- bbw::recode(var = ha.where,
recodes = "5=1;NA=NA;else=0")
ha.eho <- bbw::recode(var = ha.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ha.dry <- as.integer(df$ancpast_ha_dist_dry)
ha.dry.lt15 <- bbw::recode(var = ha.dry,
recodes = "1=1;NA=NA;else=0")
ha.dry.gteq15lt60 <- bbw::recode(var = ha.dry,
recodes = "2=1;NA=NA;else=0")
ha.dry.gteq60lt120 <- bbw::recode(var = ha.dry,
recodes = "3=1;NA=NA;else=0")
ha.dry.gteq120lt360 <- bbw::recode(var = ha.dry,
recodes = "4=1;NA=NA;else=0")
ha.dry.gteq360lt720 <- bbw::recode(var = ha.dry,
recodes = "5=1;NA=NA;else=0")
ha.dry.gteq720lt1440 <- bbw::recode(var = ha.dry,
recodes = "6=1;NA=NA;else=0")
ha.dry.gteq1440 <- bbw::recode(var = ha.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ha.wet <- as.integer(df$ancpast_ha_dist_wet)
ha.wet.lt15 <- bbw::recode(var = ha.wet,
recodes = "1=1;NA=NA;else=0")
ha.wet.gteq15lt60 <- bbw::recode(var = ha.wet,
recodes = "2=1;NA=NA;else=0")
ha.wet.gteq60lt120 <- bbw::recode(var = ha.wet,
recodes = "3=1;NA=NA;else=0")
ha.wet.gteq120lt360 <- bbw::recode(var = ha.wet,
recodes = "4=1;NA=NA;else=0")
ha.wet.gteq360lt720 <- bbw::recode(var = ha.wet,
recodes = "5=1;NA=NA;else=0")
ha.wet.gteq720lt1440 <- bbw::recode(var = ha.wet,
recodes = "6=1;NA=NA;else=0")
ha.wet.gteq1440 <- bbw::recode(var = ha.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ha.visit <- as.integer(df$ancpast_ha_visit)
## Number of visits per trimester
ha.visit.first <- as.integer(df$ancpast_ha_1tri_times)
ha.visit.second <- as.integer(df$ancpast_ha_2tri_times)
ha.visit.third <- as.integer(df$ancpast_ha_3tri_times)
## Concatenate ha provider data.frame
ha <- data.frame(ha, ha.where, ha.home,
ha.gov, ha.private, ha.srhc,
ha.village, ha.eho, ha.dry,
ha.dry.lt15, ha.dry.gteq15lt60,
ha.dry.gteq60lt120, ha.dry.gteq120lt360,
ha.dry.gteq360lt720, ha.dry.gteq720lt1440,
ha.dry.gteq1440, ha.wet,
ha.wet.lt15, ha.wet.gteq15lt60,
ha.wet.gteq60lt120, ha.wet.gteq120lt360,
ha.wet.gteq360lt720, ha.wet.gteq720lt1440,
ha.wet.gteq1440, ha.visit,
ha.visit.first, ha.visit.second,
ha.visit.third)
}
## Return data.frame
return(ha)
}
################################################################################
#
#' Function to recode the private doctor ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded private doctor ANC provider information
#'
#' @examples
#' ## Recode private doctor provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_pdoc(df = x, status = "current")
#'
#' ## Recode private doctor provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_pdoc(df = x, status = "past")
#' @export
#'
#'
#
################################################################################
recode_provider_pdoc <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend pdoc
pdoc <- as.integer(df$ancnow_who.5)
## Where pdoc
pdoc.where <- as.integer(df$ancnow_pdoc_where)
pdoc.home <- bbw::recode(var = pdoc.where,
recodes = "1=1;NA=NA;else=0")
pdoc.gov <- bbw::recode(var = pdoc.where,
recodes = "2=1;NA=NA;else=0")
pdoc.private <- bbw::recode(var = pdoc.where,
recodes = "3=1;NA=NA;else=0")
pdoc.srhc <- bbw::recode(var = pdoc.where,
recodes = "4=1;NA=NA;else=0")
pdoc.village <- bbw::recode(var = pdoc.where,
recodes = "5=1;NA=NA;else=0")
pdoc.eho <- bbw::recode(var = pdoc.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
pdoc.dry <- as.integer(df$ancnow_pdoc_dist_dry)
pdoc.dry.lt15 <- bbw::recode(var = pdoc.dry,
recodes = "1=1;NA=NA;else=0")
pdoc.dry.gteq15lt60 <- bbw::recode(var = pdoc.dry,
recodes = "2=1;NA=NA;else=0")
pdoc.dry.gteq60lt120 <- bbw::recode(var = pdoc.dry,
recodes = "3=1;NA=NA;else=0")
pdoc.dry.gteq120lt360 <- bbw::recode(var = pdoc.dry,
recodes = "4=1;NA=NA;else=0")
pdoc.dry.gteq360lt720 <- bbw::recode(var = pdoc.dry,
recodes = "5=1;NA=NA;else=0")
pdoc.dry.gteq720lt1440 <- bbw::recode(var = pdoc.dry,
recodes = "6=1;NA=NA;else=0")
pdoc.dry.gteq1440 <- bbw::recode(var = pdoc.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
pdoc.wet <- as.integer(df$ancnow_pdoc_dist_wet)
pdoc.wet.lt15 <- bbw::recode(var = pdoc.wet,
recodes = "1=1;NA=NA;else=0")
pdoc.wet.gteq15lt60 <- bbw::recode(var = pdoc.wet,
recodes = "2=1;NA=NA;else=0")
pdoc.wet.gteq60lt120 <- bbw::recode(var = pdoc.wet,
recodes = "3=1;NA=NA;else=0")
pdoc.wet.gteq120lt360 <- bbw::recode(var = pdoc.wet,
recodes = "4=1;NA=NA;else=0")
pdoc.wet.gteq360lt720 <- bbw::recode(var = pdoc.wet,
recodes = "5=1;NA=NA;else=0")
pdoc.wet.gteq720lt1440 <- bbw::recode(var = pdoc.wet,
recodes = "6=1;NA=NA;else=0")
pdoc.wet.gteq1440 <- bbw::recode(var = pdoc.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
pdoc.visit <- as.integer(df$ancnow_pdoc_visit)
## Number of visits per trimester
pdoc.visit.first <- as.integer(df$ancnow_pdoc_1tri_times)
pdoc.visit.second <- as.integer(df$ancnow_pdoc_2tri_times)
pdoc.visit.third <- as.integer(df$ancnow_pdoc_3tri_times)
## Concatenate pdoc provider data.frame
pdoc <- data.frame(pdoc, pdoc.where, pdoc.home,
pdoc.gov, pdoc.private, pdoc.srhc,
pdoc.village, pdoc.eho, pdoc.dry,
pdoc.dry.lt15, pdoc.dry.gteq15lt60,
pdoc.dry.gteq60lt120, pdoc.dry.gteq120lt360,
pdoc.dry.gteq360lt720, pdoc.dry.gteq720lt1440,
pdoc.dry.gteq1440, pdoc.wet,
pdoc.wet.lt15, pdoc.wet.gteq15lt60,
pdoc.wet.gteq60lt120, pdoc.wet.gteq120lt360,
pdoc.wet.gteq360lt720, pdoc.wet.gteq720lt1440,
pdoc.wet.gteq1440, pdoc.visit,
pdoc.visit.first, pdoc.visit.second,
pdoc.visit.third)
} else {
## Attend pdoc
pdoc <- as.integer(df$ancpast_who.5)
## Where pdoc
pdoc.where <- as.integer(df$ancpast_pdoc_where)
pdoc.home <- bbw::recode(var = pdoc.where,
recodes = "1=1;NA=NA;else=0")
pdoc.gov <- bbw::recode(var = pdoc.where,
recodes = "2=1;NA=NA;else=0")
pdoc.private <- bbw::recode(var = pdoc.where,
recodes = "3=1;NA=NA;else=0")
pdoc.srhc <- bbw::recode(var = pdoc.where,
recodes = "4=1;NA=NA;else=0")
pdoc.village <- bbw::recode(var = pdoc.where,
recodes = "5=1;NA=NA;else=0")
pdoc.eho <- bbw::recode(var = pdoc.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
pdoc.dry <- as.integer(df$ancpast_pdoc_dist_dry)
pdoc.dry.lt15 <- bbw::recode(var = pdoc.dry,
recodes = "1=1;NA=NA;else=0")
pdoc.dry.gteq15lt60 <- bbw::recode(var = pdoc.dry,
recodes = "2=1;NA=NA;else=0")
pdoc.dry.gteq60lt120 <- bbw::recode(var = pdoc.dry,
recodes = "3=1;NA=NA;else=0")
pdoc.dry.gteq120lt360 <- bbw::recode(var = pdoc.dry,
recodes = "4=1;NA=NA;else=0")
pdoc.dry.gteq360lt720 <- bbw::recode(var = pdoc.dry,
recodes = "5=1;NA=NA;else=0")
pdoc.dry.gteq720lt1440 <- bbw::recode(var = pdoc.dry,
recodes = "6=1;NA=NA;else=0")
pdoc.dry.gteq1440 <- bbw::recode(var = pdoc.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
pdoc.wet <- as.integer(df$ancpast_pdoc_dist_wet)
pdoc.wet.lt15 <- bbw::recode(var = pdoc.wet,
recodes = "1=1;NA=NA;else=0")
pdoc.wet.gteq15lt60 <- bbw::recode(var = pdoc.wet,
recodes = "2=1;NA=NA;else=0")
pdoc.wet.gteq60lt120 <- bbw::recode(var = pdoc.wet,
recodes = "3=1;NA=NA;else=0")
pdoc.wet.gteq120lt360 <- bbw::recode(var = pdoc.wet,
recodes = "4=1;NA=NA;else=0")
pdoc.wet.gteq360lt720 <- bbw::recode(var = pdoc.wet,
recodes = "5=1;NA=NA;else=0")
pdoc.wet.gteq720lt1440 <- bbw::recode(var = pdoc.wet,
recodes = "6=1;NA=NA;else=0")
pdoc.wet.gteq1440 <- bbw::recode(var = pdoc.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
pdoc.visit <- as.integer(df$ancpast_pdoc_visit)
## Number of visits per trimester
pdoc.visit.first <- as.integer(df$ancpast_pdoc_1tri_times)
pdoc.visit.second <- as.integer(df$ancpast_pdoc_2tri_times)
pdoc.visit.third <- as.integer(df$ancpast_pdoc_3tri_times)
## Concatenate pdoc provider data.frame
pdoc <- data.frame(pdoc, pdoc.where, pdoc.home,
pdoc.gov, pdoc.private, pdoc.srhc,
pdoc.village, pdoc.eho, pdoc.dry,
pdoc.dry.lt15, pdoc.dry.gteq15lt60,
pdoc.dry.gteq60lt120, pdoc.dry.gteq120lt360,
pdoc.dry.gteq360lt720, pdoc.dry.gteq720lt1440,
pdoc.dry.gteq1440, pdoc.wet,
pdoc.wet.lt15, pdoc.wet.gteq15lt60,
pdoc.wet.gteq60lt120, pdoc.wet.gteq120lt360,
pdoc.wet.gteq360lt720, pdoc.wet.gteq720lt1440,
pdoc.wet.gteq1440, pdoc.visit,
pdoc.visit.first, pdoc.visit.second,
pdoc.visit.third)
}
## Return data.frame
return(pdoc)
}
################################################################################
#
#' Function to recode the lady health visitor ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded lady health visitor ANC provider information
#'
#' @examples
#' ## Recode lady health visitor provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_lhv(df = x, status = "current")
#'
#' ## Recode lady health visitor provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_lhv(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_lhv <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend lhv
lhv <- as.integer(df$ancnow_who.6)
## Where lhv
lhv.where <- as.integer(df$ancnow_lhv_where)
lhv.home <- bbw::recode(var = lhv.where,
recodes = "1=1;NA=NA;else=0")
lhv.gov <- bbw::recode(var = lhv.where,
recodes = "2=1;NA=NA;else=0")
lhv.private <- bbw::recode(var = lhv.where,
recodes = "3=1;NA=NA;else=0")
lhv.srhc <- bbw::recode(var = lhv.where,
recodes = "4=1;NA=NA;else=0")
lhv.village <- bbw::recode(var = lhv.where,
recodes = "5=1;NA=NA;else=0")
lhv.eho <- bbw::recode(var = lhv.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
lhv.dry <- as.integer(df$ancnow_lhv_dist_dry)
lhv.dry.lt15 <- bbw::recode(var = lhv.dry,
recodes = "1=1;NA=NA;else=0")
lhv.dry.gteq15lt60 <- bbw::recode(var = lhv.dry,
recodes = "2=1;NA=NA;else=0")
lhv.dry.gteq60lt120 <- bbw::recode(var = lhv.dry,
recodes = "3=1;NA=NA;else=0")
lhv.dry.gteq120lt360 <- bbw::recode(var = lhv.dry,
recodes = "4=1;NA=NA;else=0")
lhv.dry.gteq360lt720 <- bbw::recode(var = lhv.dry,
recodes = "5=1;NA=NA;else=0")
lhv.dry.gteq720lt1440 <- bbw::recode(var = lhv.dry,
recodes = "6=1;NA=NA;else=0")
lhv.dry.gteq1440 <- bbw::recode(var = lhv.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
lhv.wet <- as.integer(df$ancnow_lhv_dist_wet)
lhv.wet.lt15 <- bbw::recode(var = lhv.wet,
recodes = "1=1;NA=NA;else=0")
lhv.wet.gteq15lt60 <- bbw::recode(var = lhv.wet,
recodes = "2=1;NA=NA;else=0")
lhv.wet.gteq60lt120 <- bbw::recode(var = lhv.wet,
recodes = "3=1;NA=NA;else=0")
lhv.wet.gteq120lt360 <- bbw::recode(var = lhv.wet,
recodes = "4=1;NA=NA;else=0")
lhv.wet.gteq360lt720 <- bbw::recode(var = lhv.wet,
recodes = "5=1;NA=NA;else=0")
lhv.wet.gteq720lt1440 <- bbw::recode(var = lhv.wet,
recodes = "6=1;NA=NA;else=0")
lhv.wet.gteq1440 <- bbw::recode(var = lhv.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
lhv.visit <- as.integer(df$ancnow_lhv_visit)
## Number of visits per trimester
lhv.visit.first <- as.integer(df$ancnow_lhv_1tri_times)
lhv.visit.second <- as.integer(df$ancnow_lhv_2tri_times)
lhv.visit.third <- as.integer(df$ancnow_lhv_3tri_times)
## Concatenate lhv provider data.frame
lhv <- data.frame(lhv, lhv.where, lhv.home,
lhv.gov, lhv.private, lhv.srhc,
lhv.village, lhv.eho, lhv.dry,
lhv.dry.lt15, lhv.dry.gteq15lt60,
lhv.dry.gteq60lt120, lhv.dry.gteq120lt360,
lhv.dry.gteq360lt720, lhv.dry.gteq720lt1440,
lhv.dry.gteq1440, lhv.wet,
lhv.wet.lt15, lhv.wet.gteq15lt60,
lhv.wet.gteq60lt120, lhv.wet.gteq120lt360,
lhv.wet.gteq360lt720, lhv.wet.gteq720lt1440,
lhv.wet.gteq1440, lhv.visit,
lhv.visit.first, lhv.visit.second,
lhv.visit.third)
} else {
## Attend lhv
lhv <- as.integer(df$ancpast_who.6)
## Where lhv
lhv.where <- as.integer(df$ancpast_lhv_where)
lhv.home <- bbw::recode(var = lhv.where,
recodes = "1=1;NA=NA;else=0")
lhv.gov <- bbw::recode(var = lhv.where,
recodes = "2=1;NA=NA;else=0")
lhv.private <- bbw::recode(var = lhv.where,
recodes = "3=1;NA=NA;else=0")
lhv.srhc <- bbw::recode(var = lhv.where,
recodes = "4=1;NA=NA;else=0")
lhv.village <- bbw::recode(var = lhv.where,
recodes = "5=1;NA=NA;else=0")
lhv.eho <- bbw::recode(var = lhv.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
lhv.dry <- as.integer(df$ancpast_lhv_dist_dry)
lhv.dry.lt15 <- bbw::recode(var = lhv.dry,
recodes = "1=1;NA=NA;else=0")
lhv.dry.gteq15lt60 <- bbw::recode(var = lhv.dry,
recodes = "2=1;NA=NA;else=0")
lhv.dry.gteq60lt120 <- bbw::recode(var = lhv.dry,
recodes = "3=1;NA=NA;else=0")
lhv.dry.gteq120lt360 <- bbw::recode(var = lhv.dry,
recodes = "4=1;NA=NA;else=0")
lhv.dry.gteq360lt720 <- bbw::recode(var = lhv.dry,
recodes = "5=1;NA=NA;else=0")
lhv.dry.gteq720lt1440 <- bbw::recode(var = lhv.dry,
recodes = "6=1;NA=NA;else=0")
lhv.dry.gteq1440 <- bbw::recode(var = lhv.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
lhv.wet <- as.integer(df$ancpast_lhv_dist_wet)
lhv.wet.lt15 <- bbw::recode(var = lhv.wet,
recodes = "1=1;NA=NA;else=0")
lhv.wet.gteq15lt60 <- bbw::recode(var = lhv.wet,
recodes = "2=1;NA=NA;else=0")
lhv.wet.gteq60lt120 <- bbw::recode(var = lhv.wet,
recodes = "3=1;NA=NA;else=0")
lhv.wet.gteq120lt360 <- bbw::recode(var = lhv.wet,
recodes = "4=1;NA=NA;else=0")
lhv.wet.gteq360lt720 <- bbw::recode(var = lhv.wet,
recodes = "5=1;NA=NA;else=0")
lhv.wet.gteq720lt1440 <- bbw::recode(var = lhv.wet,
recodes = "6=1;NA=NA;else=0")
lhv.wet.gteq1440 <- bbw::recode(var = lhv.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
lhv.visit <- as.integer(df$ancpast_lhv_visit)
## Number of visits per trimester
lhv.visit.first <- as.integer(df$ancpast_lhv_1tri_times)
lhv.visit.second <- as.integer(df$ancpast_lhv_2tri_times)
lhv.visit.third <- as.integer(df$ancpast_lhv_3tri_times)
## Concatenate lhv provider data.frame
lhv <- data.frame(lhv, lhv.where, lhv.home,
lhv.gov, lhv.private, lhv.srhc,
lhv.village, lhv.eho, lhv.dry,
lhv.dry.lt15, lhv.dry.gteq15lt60,
lhv.dry.gteq60lt120, lhv.dry.gteq120lt360,
lhv.dry.gteq360lt720, lhv.dry.gteq720lt1440,
lhv.dry.gteq1440, lhv.wet,
lhv.wet.lt15, lhv.wet.gteq15lt60,
lhv.wet.gteq60lt120, lhv.wet.gteq120lt360,
lhv.wet.gteq360lt720, lhv.wet.gteq720lt1440,
lhv.wet.gteq1440, lhv.visit,
lhv.visit.first, lhv.visit.second,
lhv.visit.third)
}
## Return data.frame
return(lhv)
}
################################################################################
#
#' Function to recode the midwife ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded midwife ANC provider information
#'
#' @examples
#' ## Recode midwife provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_midwife(df = x, status = "current")
#'
#' ## Recode midwife provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_midwife(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_midwife <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend midwife
midwife <- as.integer(df$ancnow_who.7)
## Where midwife
midwife.where <- as.integer(df$ancnow_mw_where)
midwife.home <- bbw::recode(var = midwife.where,
recodes = "1=1;NA=NA;else=0")
midwife.gov <- bbw::recode(var = midwife.where,
recodes = "2=1;NA=NA;else=0")
midwife.private <- bbw::recode(var = midwife.where,
recodes = "3=1;NA=NA;else=0")
midwife.srhc <- bbw::recode(var = midwife.where,
recodes = "4=1;NA=NA;else=0")
midwife.village <- bbw::recode(var = midwife.where,
recodes = "5=1;NA=NA;else=0")
midwife.eho <- bbw::recode(var = midwife.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
midwife.dry <- as.integer(df$ancnow_mw_dist_dry)
midwife.dry.lt15 <- bbw::recode(var = midwife.dry,
recodes = "1=1;NA=NA;else=0")
midwife.dry.gteq15lt60 <- bbw::recode(var = midwife.dry,
recodes = "2=1;NA=NA;else=0")
midwife.dry.gteq60lt120 <- bbw::recode(var = midwife.dry,
recodes = "3=1;NA=NA;else=0")
midwife.dry.gteq120lt360 <- bbw::recode(var = midwife.dry,
recodes = "4=1;NA=NA;else=0")
midwife.dry.gteq360lt720 <- bbw::recode(var = midwife.dry,
recodes = "5=1;NA=NA;else=0")
midwife.dry.gteq720lt1440 <- bbw::recode(var = midwife.dry,
recodes = "6=1;NA=NA;else=0")
midwife.dry.gteq1440 <- bbw::recode(var = midwife.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
midwife.wet <- as.integer(df$ancnow_mw_dist_wet)
midwife.wet.lt15 <- bbw::recode(var = midwife.wet,
recodes = "1=1;NA=NA;else=0")
midwife.wet.gteq15lt60 <- bbw::recode(var = midwife.wet,
recodes = "2=1;NA=NA;else=0")
midwife.wet.gteq60lt120 <- bbw::recode(var = midwife.wet,
recodes = "3=1;NA=NA;else=0")
midwife.wet.gteq120lt360 <- bbw::recode(var = midwife.wet,
recodes = "4=1;NA=NA;else=0")
midwife.wet.gteq360lt720 <- bbw::recode(var = midwife.wet,
recodes = "5=1;NA=NA;else=0")
midwife.wet.gteq720lt1440 <- bbw::recode(var = midwife.wet,
recodes = "6=1;NA=NA;else=0")
midwife.wet.gteq1440 <- bbw::recode(var = midwife.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
midwife.visit <- as.integer(df$ancnow_mw_visit)
## Number of visits per trimester
midwife.visit.first <- as.integer(df$ancnow_mw_1tri_times)
midwife.visit.second <- as.integer(df$ancnow_mw_2tri_times)
midwife.visit.third <- as.integer(df$ancnow_mw_3tri_times)
## Concatenate midwife provider data.frame
midwife <- data.frame(midwife, midwife.where, midwife.home,
midwife.gov, midwife.private, midwife.srhc,
midwife.village, midwife.eho, midwife.dry,
midwife.dry.lt15, midwife.dry.gteq15lt60,
midwife.dry.gteq60lt120, midwife.dry.gteq120lt360,
midwife.dry.gteq360lt720, midwife.dry.gteq720lt1440,
midwife.dry.gteq1440, midwife.wet,
midwife.wet.lt15, midwife.wet.gteq15lt60,
midwife.wet.gteq60lt120, midwife.wet.gteq120lt360,
midwife.wet.gteq360lt720, midwife.wet.gteq720lt1440,
midwife.wet.gteq1440, midwife.visit,
midwife.visit.first, midwife.visit.second,
midwife.visit.third)
} else {
## Attend midwife
midwife <- as.integer(df$ancpast_who.7)
## Where midwife
midwife.where <- as.integer(df$ancpast_mw_where)
midwife.home <- bbw::recode(var = midwife.where,
recodes = "1=1;NA=NA;else=0")
midwife.gov <- bbw::recode(var = midwife.where,
recodes = "2=1;NA=NA;else=0")
midwife.private <- bbw::recode(var = midwife.where,
recodes = "3=1;NA=NA;else=0")
midwife.srhc <- bbw::recode(var = midwife.where,
recodes = "4=1;NA=NA;else=0")
midwife.village <- bbw::recode(var = midwife.where,
recodes = "5=1;NA=NA;else=0")
midwife.eho <- bbw::recode(var = midwife.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
midwife.dry <- as.integer(df$ancpast_mw_dist_dry)
midwife.dry.lt15 <- bbw::recode(var = midwife.dry,
recodes = "1=1;NA=NA;else=0")
midwife.dry.gteq15lt60 <- bbw::recode(var = midwife.dry,
recodes = "2=1;NA=NA;else=0")
midwife.dry.gteq60lt120 <- bbw::recode(var = midwife.dry,
recodes = "3=1;NA=NA;else=0")
midwife.dry.gteq120lt360 <- bbw::recode(var = midwife.dry,
recodes = "4=1;NA=NA;else=0")
midwife.dry.gteq360lt720 <- bbw::recode(var = midwife.dry,
recodes = "5=1;NA=NA;else=0")
midwife.dry.gteq720lt1440 <- bbw::recode(var = midwife.dry,
recodes = "6=1;NA=NA;else=0")
midwife.dry.gteq1440 <- bbw::recode(var = midwife.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
midwife.wet <- as.integer(df$ancpast_mw_dist_wet)
midwife.wet.lt15 <- bbw::recode(var = midwife.wet,
recodes = "1=1;NA=NA;else=0")
midwife.wet.gteq15lt60 <- bbw::recode(var = midwife.wet,
recodes = "2=1;NA=NA;else=0")
midwife.wet.gteq60lt120 <- bbw::recode(var = midwife.wet,
recodes = "3=1;NA=NA;else=0")
midwife.wet.gteq120lt360 <- bbw::recode(var = midwife.wet,
recodes = "4=1;NA=NA;else=0")
midwife.wet.gteq360lt720 <- bbw::recode(var = midwife.wet,
recodes = "5=1;NA=NA;else=0")
midwife.wet.gteq720lt1440 <- bbw::recode(var = midwife.wet,
recodes = "6=1;NA=NA;else=0")
midwife.wet.gteq1440 <- bbw::recode(var = midwife.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
midwife.visit <- as.integer(df$ancpast_mw_visit)
## Number of visits per trimester
midwife.visit.first <- as.integer(df$ancpast_mw_1tri_times)
midwife.visit.second <- as.integer(df$ancpast_mw_2tri_times)
midwife.visit.third <- as.integer(df$ancpast_mw_3tri_times)
## Concatenate midwife provider data.frame
midwife <- data.frame(midwife, midwife.where, midwife.home,
midwife.gov, midwife.private, midwife.srhc,
midwife.village, midwife.eho, midwife.dry,
midwife.dry.lt15, midwife.dry.gteq15lt60,
midwife.dry.gteq60lt120, midwife.dry.gteq120lt360,
midwife.dry.gteq360lt720, midwife.dry.gteq720lt1440,
midwife.dry.gteq1440, midwife.wet,
midwife.wet.lt15, midwife.wet.gteq15lt60,
midwife.wet.gteq60lt120, midwife.wet.gteq120lt360,
midwife.wet.gteq360lt720, midwife.wet.gteq720lt1440,
midwife.wet.gteq1440, midwife.visit,
midwife.visit.first, midwife.visit.second,
midwife.visit.third)
}
## Return data.frame
return(midwife)
}
################################################################################
#
#' Function to recode the auxilliary midwife ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded auxilliary midwife ANC provider information
#'
#' @examples
#' ## Recode auxilliary midwife for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_amw(df = x, status = "current")
#'
#' ## Recode auxilliary midwife for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_amw(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_amw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend amw
amw <- as.integer(df$ancnow_who.8)
## Where amw
amw.where <- as.integer(df$ancnow_amw_where)
amw.home <- bbw::recode(var = amw.where, recodes = "1=1;NA=NA;else=0")
amw.gov <- bbw::recode(var = amw.where, recodes = "2=1;NA=NA;else=0")
amw.private <- bbw::recode(var = amw.where, recodes = "3=1;NA=NA;else=0")
amw.srhc <- bbw::recode(var = amw.where, recodes = "4=1;NA=NA;else=0")
amw.village <- bbw::recode(var = amw.where, recodes = "5=1;NA=NA;else=0")
amw.eho <- bbw::recode(var = amw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
amw.dry <- as.integer(df$ancnow_amw_dist_dry)
amw.dry.lt15 <- bbw::recode(var = amw.dry,
recodes = "1=1;NA=NA;else=0")
amw.dry.gteq15lt60 <- bbw::recode(var = amw.dry,
recodes = "2=1;NA=NA;else=0")
amw.dry.gteq60lt120 <- bbw::recode(var = amw.dry,
recodes = "3=1;NA=NA;else=0")
amw.dry.gteq120lt360 <- bbw::recode(var = amw.dry,
recodes = "4=1;NA=NA;else=0")
amw.dry.gteq360lt720 <- bbw::recode(var = amw.dry,
recodes = "5=1;NA=NA;else=0")
amw.dry.gteq720lt1440 <- bbw::recode(var = amw.dry,
recodes = "6=1;NA=NA;else=0")
amw.dry.gteq1440 <- bbw::recode(var = amw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
amw.wet <- as.integer(df$ancnow_amw_dist_wet)
amw.wet.lt15 <- bbw::recode(var = amw.wet,
recodes = "1=1;NA=NA;else=0")
amw.wet.gteq15lt60 <- bbw::recode(var = amw.wet,
recodes = "2=1;NA=NA;else=0")
amw.wet.gteq60lt120 <- bbw::recode(var = amw.wet,
recodes = "3=1;NA=NA;else=0")
amw.wet.gteq120lt360 <- bbw::recode(var = amw.wet,
recodes = "4=1;NA=NA;else=0")
amw.wet.gteq360lt720 <- bbw::recode(var = amw.wet,
recodes = "5=1;NA=NA;else=0")
amw.wet.gteq720lt1440 <- bbw::recode(var = amw.wet,
recodes = "6=1;NA=NA;else=0")
amw.wet.gteq1440 <- bbw::recode(var = amw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
amw.visit <- as.integer(df$ancnow_amw_visit)
## Number of visits per trimester
amw.visit.first <- as.integer(df$ancnow_amw_1tri_times)
amw.visit.second <- as.integer(df$ancnow_amw_2tri_times)
amw.visit.third <- as.integer(df$ancnow_amw_3tri_times)
## Concatenate amw provider data.frame
amw <- data.frame(amw, amw.where, amw.home,
amw.gov, amw.private, amw.srhc,
amw.village, amw.eho, amw.dry,
amw.dry.lt15, amw.dry.gteq15lt60,
amw.dry.gteq60lt120, amw.dry.gteq120lt360,
amw.dry.gteq360lt720, amw.dry.gteq720lt1440,
amw.dry.gteq1440, amw.wet,
amw.wet.lt15, amw.wet.gteq15lt60,
amw.wet.gteq60lt120, amw.wet.gteq120lt360,
amw.wet.gteq360lt720, amw.wet.gteq720lt1440,
amw.wet.gteq1440, amw.visit,
amw.visit.first, amw.visit.second,
amw.visit.third)
} else {
## Attend amw
amw <- as.integer(df$ancpast_who.8)
## Where amw
amw.where <- as.integer(df$ancpast_amw_where)
amw.home <- bbw::recode(var = amw.where, recodes = "1=1;NA=NA;else=0")
amw.gov <- bbw::recode(var = amw.where, recodes = "2=1;NA=NA;else=0")
amw.private <- bbw::recode(var = amw.where, recodes = "3=1;NA=NA;else=0")
amw.srhc <- bbw::recode(var = amw.where, recodes = "4=1;NA=NA;else=0")
amw.village <- bbw::recode(var = amw.where, recodes = "5=1;NA=NA;else=0")
amw.eho <- bbw::recode(var = amw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
amw.dry <- as.integer(df$ancpast_amw_dist_dry)
amw.dry.lt15 <- bbw::recode(var = amw.dry,
recodes = "1=1;NA=NA;else=0")
amw.dry.gteq15lt60 <- bbw::recode(var = amw.dry,
recodes = "2=1;NA=NA;else=0")
amw.dry.gteq60lt120 <- bbw::recode(var = amw.dry,
recodes = "3=1;NA=NA;else=0")
amw.dry.gteq120lt360 <- bbw::recode(var = amw.dry,
recodes = "4=1;NA=NA;else=0")
amw.dry.gteq360lt720 <- bbw::recode(var = amw.dry,
recodes = "5=1;NA=NA;else=0")
amw.dry.gteq720lt1440 <- bbw::recode(var = amw.dry,
recodes = "6=1;NA=NA;else=0")
amw.dry.gteq1440 <- bbw::recode(var = amw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
amw.wet <- as.integer(df$ancpast_amw_dist_wet)
amw.wet.lt15 <- bbw::recode(var = amw.wet,
recodes = "1=1;NA=NA;else=0")
amw.wet.gteq15lt60 <- bbw::recode(var = amw.wet,
recodes = "2=1;NA=NA;else=0")
amw.wet.gteq60lt120 <- bbw::recode(var = amw.wet,
recodes = "3=1;NA=NA;else=0")
amw.wet.gteq120lt360 <- bbw::recode(var = amw.wet,
recodes = "4=1;NA=NA;else=0")
amw.wet.gteq360lt720 <- bbw::recode(var = amw.wet,
recodes = "5=1;NA=NA;else=0")
amw.wet.gteq720lt1440 <- bbw::recode(var = amw.wet,
recodes = "6=1;NA=NA;else=0")
amw.wet.gteq1440 <- bbw::recode(var = amw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
amw.visit <- as.integer(df$ancpast_amw_visit)
## Number of visits per trimester
amw.visit.first <- as.integer(df$ancpast_amw_1tri_times)
amw.visit.second <- as.integer(df$ancpast_amw_2tri_times)
amw.visit.third <- as.integer(df$ancpast_amw_3tri_times)
## Concatenate amw provider data.frame
amw <- data.frame(amw, amw.where, amw.home,
amw.gov, amw.private, amw.srhc,
amw.village, amw.eho, amw.dry,
amw.dry.lt15, amw.dry.gteq15lt60,
amw.dry.gteq60lt120, amw.dry.gteq120lt360,
amw.dry.gteq360lt720, amw.dry.gteq720lt1440,
amw.dry.gteq1440, amw.wet,
amw.wet.lt15, amw.wet.gteq15lt60,
amw.wet.gteq60lt120, amw.wet.gteq120lt360,
amw.wet.gteq360lt720, amw.wet.gteq720lt1440,
amw.wet.gteq1440, amw.visit,
amw.visit.first, amw.visit.second,
amw.visit.third)
}
## Return data.frame
return(amw)
}
################################################################################
#
#' Function to recode the traditional birth attendant ANC provider data for the
#' Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded traditional birth attendant ANC provider
#' information
#'
#' @examples
#' ## Recode tba provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_tba(df = x, status = "current")
#'
#' ## Recode tba provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_tba(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_tba <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend tba
tba <- as.integer(df$ancnow_who.9)
## Where tba
tba.where <- as.integer(df$ancnow_tba_where)
tba.home <- bbw::recode(var = tba.where, recodes = "1=1;NA=NA;else=0")
tba.gov <- bbw::recode(var = tba.where, recodes = "2=1;NA=NA;else=0")
tba.private <- bbw::recode(var = tba.where, recodes = "3=1;NA=NA;else=0")
tba.srhc <- bbw::recode(var = tba.where, recodes = "4=1;NA=NA;else=0")
tba.village <- bbw::recode(var = tba.where, recodes = "5=1;NA=NA;else=0")
tba.eho <- bbw::recode(var = tba.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
tba.dry <- as.integer(df$ancnow_tba_dist_dry)
tba.dry.lt15 <- bbw::recode(var = tba.dry,
recodes = "1=1;NA=NA;else=0")
tba.dry.gteq15lt60 <- bbw::recode(var = tba.dry,
recodes = "2=1;NA=NA;else=0")
tba.dry.gteq60lt120 <- bbw::recode(var = tba.dry,
recodes = "3=1;NA=NA;else=0")
tba.dry.gteq120lt360 <- bbw::recode(var = tba.dry,
recodes = "4=1;NA=NA;else=0")
tba.dry.gteq360lt720 <- bbw::recode(var = tba.dry,
recodes = "5=1;NA=NA;else=0")
tba.dry.gteq720lt1440 <- bbw::recode(var = tba.dry,
recodes = "6=1;NA=NA;else=0")
tba.dry.gteq1440 <- bbw::recode(var = tba.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
tba.wet <- as.integer(df$ancnow_tba_dist_wet)
tba.wet.lt15 <- bbw::recode(var = tba.wet,
recodes = "1=1;NA=NA;else=0")
tba.wet.gteq15lt60 <- bbw::recode(var = tba.wet,
recodes = "2=1;NA=NA;else=0")
tba.wet.gteq60lt120 <- bbw::recode(var = tba.wet,
recodes = "3=1;NA=NA;else=0")
tba.wet.gteq120lt360 <- bbw::recode(var = tba.wet,
recodes = "4=1;NA=NA;else=0")
tba.wet.gteq360lt720 <- bbw::recode(var = tba.wet,
recodes = "5=1;NA=NA;else=0")
tba.wet.gteq720lt1440 <- bbw::recode(var = tba.wet,
recodes = "6=1;NA=NA;else=0")
tba.wet.gteq1440 <- bbw::recode(var = tba.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
tba.visit <- as.integer(df$ancnow_tba_visit)
## Number of visits per trimester
tba.visit.first <- as.integer(df$ancnow_tba_1tri_times)
tba.visit.second <- as.integer(df$ancnow_tba_2tri_times)
tba.visit.third <- as.integer(df$ancnow_tba_3tri_times)
## Concatenate tba provider data.frame
tba <- data.frame(tba, tba.where, tba.home,
tba.gov, tba.private, tba.srhc,
tba.village, tba.eho, tba.dry,
tba.dry.lt15, tba.dry.gteq15lt60,
tba.dry.gteq60lt120, tba.dry.gteq120lt360,
tba.dry.gteq360lt720, tba.dry.gteq720lt1440,
tba.dry.gteq1440, tba.wet,
tba.wet.lt15, tba.wet.gteq15lt60,
tba.wet.gteq60lt120, tba.wet.gteq120lt360,
tba.wet.gteq360lt720, tba.wet.gteq720lt1440,
tba.wet.gteq1440, tba.visit,
tba.visit.first, tba.visit.second,
tba.visit.third)
} else {
## Attend tba
tba <- as.integer(df$ancpast_who.9)
## Where tba
tba.where <- as.integer(df$ancpast_tba_where)
tba.home <- bbw::recode(var = tba.where, recodes = "1=1;NA=NA;else=0")
tba.gov <- bbw::recode(var = tba.where, recodes = "2=1;NA=NA;else=0")
tba.private <- bbw::recode(var = tba.where, recodes = "3=1;NA=NA;else=0")
tba.srhc <- bbw::recode(var = tba.where, recodes = "4=1;NA=NA;else=0")
tba.village <- bbw::recode(var = tba.where, recodes = "5=1;NA=NA;else=0")
tba.eho <- bbw::recode(var = tba.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
tba.dry <- as.integer(df$ancpast_tba_dist_dry)
tba.dry.lt15 <- bbw::recode(var = tba.dry,
recodes = "1=1;NA=NA;else=0")
tba.dry.gteq15lt60 <- bbw::recode(var = tba.dry,
recodes = "2=1;NA=NA;else=0")
tba.dry.gteq60lt120 <- bbw::recode(var = tba.dry,
recodes = "3=1;NA=NA;else=0")
tba.dry.gteq120lt360 <- bbw::recode(var = tba.dry,
recodes = "4=1;NA=NA;else=0")
tba.dry.gteq360lt720 <- bbw::recode(var = tba.dry,
recodes = "5=1;NA=NA;else=0")
tba.dry.gteq720lt1440 <- bbw::recode(var = tba.dry,
recodes = "6=1;NA=NA;else=0")
tba.dry.gteq1440 <- bbw::recode(var = tba.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
tba.wet <- as.integer(df$ancpast_tba_dist_wet)
tba.wet.lt15 <- bbw::recode(var = tba.wet,
recodes = "1=1;NA=NA;else=0")
tba.wet.gteq15lt60 <- bbw::recode(var = tba.wet,
recodes = "2=1;NA=NA;else=0")
tba.wet.gteq60lt120 <- bbw::recode(var = tba.wet,
recodes = "3=1;NA=NA;else=0")
tba.wet.gteq120lt360 <- bbw::recode(var = tba.wet,
recodes = "4=1;NA=NA;else=0")
tba.wet.gteq360lt720 <- bbw::recode(var = tba.wet,
recodes = "5=1;NA=NA;else=0")
tba.wet.gteq720lt1440 <- bbw::recode(var = tba.wet,
recodes = "6=1;NA=NA;else=0")
tba.wet.gteq1440 <- bbw::recode(var = tba.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
tba.visit <- as.integer(df$ancpast_tba_visit)
## Number of visits per trimester
tba.visit.first <- as.integer(df$ancpast_tba_1tri_times)
tba.visit.second <- as.integer(df$ancpast_tba_2tri_times)
tba.visit.third <- as.integer(df$ancpast_tba_3tri_times)
## Concatenate tba provider data.frame
tba <- data.frame(tba, tba.where, tba.home,
tba.gov, tba.private, tba.srhc,
tba.village, tba.eho, tba.dry,
tba.dry.lt15, tba.dry.gteq15lt60,
tba.dry.gteq60lt120, tba.dry.gteq120lt360,
tba.dry.gteq360lt720, tba.dry.gteq720lt1440,
tba.dry.gteq1440, tba.wet,
tba.wet.lt15, tba.wet.gteq15lt60,
tba.wet.gteq60lt120, tba.wet.gteq120lt360,
tba.wet.gteq360lt720, tba.wet.gteq720lt1440,
tba.wet.gteq1440, tba.visit,
tba.visit.first, tba.visit.second,
tba.visit.third)
}
## Return data.frame
return(tba)
}
################################################################################
#
#' Function to recode the community health worker ANC provider data for the
#' Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded community health worker ANC provider
#' information
#'
#' @examples
#' ## Recode chw provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_chw(df = x, status = "current")
#'
#' ## Recode chw provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_chw(df = x, status = "past")
#' @export
#'
#'
#
################################################################################
recode_provider_chw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend chw
chw <- as.integer(df$ancnow_who.10)
## Where chw
chw.where <- as.integer(df$ancnow_chw_where)
chw.home <- bbw::recode(var = chw.where, recodes = "1=1;NA=NA;else=0")
chw.gov <- bbw::recode(var = chw.where, recodes = "2=1;NA=NA;else=0")
chw.private <- bbw::recode(var = chw.where, recodes = "3=1;NA=NA;else=0")
chw.srhc <- bbw::recode(var = chw.where, recodes = "4=1;NA=NA;else=0")
chw.village <- bbw::recode(var = chw.where, recodes = "5=1;NA=NA;else=0")
chw.eho <- bbw::recode(var = chw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
chw.dry <- as.integer(df$ancnow_chw_dist_dry)
chw.dry.lt15 <- bbw::recode(var = chw.dry,
recodes = "1=1;NA=NA;else=0")
chw.dry.gteq15lt60 <- bbw::recode(var = chw.dry,
recodes = "2=1;NA=NA;else=0")
chw.dry.gteq60lt120 <- bbw::recode(var = chw.dry,
recodes = "3=1;NA=NA;else=0")
chw.dry.gteq120lt360 <- bbw::recode(var = chw.dry,
recodes = "4=1;NA=NA;else=0")
chw.dry.gteq360lt720 <- bbw::recode(var = chw.dry,
recodes = "5=1;NA=NA;else=0")
chw.dry.gteq720lt1440 <- bbw::recode(var = chw.dry,
recodes = "6=1;NA=NA;else=0")
chw.dry.gteq1440 <- bbw::recode(var = chw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
chw.wet <- as.integer(df$ancnow_chw_dist_wet)
chw.wet.lt15 <- bbw::recode(var = chw.wet,
recodes = "1=1;NA=NA;else=0")
chw.wet.gteq15lt60 <- bbw::recode(var = chw.wet,
recodes = "2=1;NA=NA;else=0")
chw.wet.gteq60lt120 <- bbw::recode(var = chw.wet,
recodes = "3=1;NA=NA;else=0")
chw.wet.gteq120lt360 <- bbw::recode(var = chw.wet,
recodes = "4=1;NA=NA;else=0")
chw.wet.gteq360lt720 <- bbw::recode(var = chw.wet,
recodes = "5=1;NA=NA;else=0")
chw.wet.gteq720lt1440 <- bbw::recode(var = chw.wet,
recodes = "6=1;NA=NA;else=0")
chw.wet.gteq1440 <- bbw::recode(var = chw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
chw.visit <- as.integer(df$ancnow_chw_visit)
## Number of visits per trimester
chw.visit.first <- as.integer(df$ancnow_chw_1tri_times)
chw.visit.second <- as.integer(df$ancnow_chw_2tri_times)
chw.visit.third <- as.integer(df$ancnow_chw_3tri_times)
## Concatenate chw provider data.frame
chw <- data.frame(chw, chw.where, chw.home,
chw.gov, chw.private, chw.srhc,
chw.village, chw.eho, chw.dry,
chw.dry.lt15, chw.dry.gteq15lt60,
chw.dry.gteq60lt120, chw.dry.gteq120lt360,
chw.dry.gteq360lt720, chw.dry.gteq720lt1440,
chw.dry.gteq1440, chw.wet,
chw.wet.lt15, chw.wet.gteq15lt60,
chw.wet.gteq60lt120, chw.wet.gteq120lt360,
chw.wet.gteq360lt720, chw.wet.gteq720lt1440,
chw.wet.gteq1440, chw.visit,
chw.visit.first, chw.visit.second,
chw.visit.third)
} else {
## Attend chw
chw <- as.integer(df$ancpast_who.10)
## Where chw
chw.where <- as.integer(df$ancpast_chw_where)
chw.home <- bbw::recode(var = chw.where, recodes = "1=1;NA=NA;else=0")
chw.gov <- bbw::recode(var = chw.where, recodes = "2=1;NA=NA;else=0")
chw.private <- bbw::recode(var = chw.where, recodes = "3=1;NA=NA;else=0")
chw.srhc <- bbw::recode(var = chw.where, recodes = "4=1;NA=NA;else=0")
chw.village <- bbw::recode(var = chw.where, recodes = "5=1;NA=NA;else=0")
chw.eho <- bbw::recode(var = chw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
chw.dry <- as.integer(df$ancpast_chw_dist_dry)
chw.dry.lt15 <- bbw::recode(var = chw.dry,
recodes = "1=1;NA=NA;else=0")
chw.dry.gteq15lt60 <- bbw::recode(var = chw.dry,
recodes = "2=1;NA=NA;else=0")
chw.dry.gteq60lt120 <- bbw::recode(var = chw.dry,
recodes = "3=1;NA=NA;else=0")
chw.dry.gteq120lt360 <- bbw::recode(var = chw.dry,
recodes = "4=1;NA=NA;else=0")
chw.dry.gteq360lt720 <- bbw::recode(var = chw.dry,
recodes = "5=1;NA=NA;else=0")
chw.dry.gteq720lt1440 <- bbw::recode(var = chw.dry,
recodes = "6=1;NA=NA;else=0")
chw.dry.gteq1440 <- bbw::recode(var = chw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
chw.wet <- as.integer(df$ancpast_chw_dist_wet)
chw.wet.lt15 <- bbw::recode(var = chw.wet,
recodes = "1=1;NA=NA;else=0")
chw.wet.gteq15lt60 <- bbw::recode(var = chw.wet,
recodes = "2=1;NA=NA;else=0")
chw.wet.gteq60lt120 <- bbw::recode(var = chw.wet,
recodes = "3=1;NA=NA;else=0")
chw.wet.gteq120lt360 <- bbw::recode(var = chw.wet,
recodes = "4=1;NA=NA;else=0")
chw.wet.gteq360lt720 <- bbw::recode(var = chw.wet,
recodes = "5=1;NA=NA;else=0")
chw.wet.gteq720lt1440 <- bbw::recode(var = chw.wet,
recodes = "6=1;NA=NA;else=0")
chw.wet.gteq1440 <- bbw::recode(var = chw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
chw.visit <- as.integer(df$ancpast_chw_visit)
## Number of visits per trimester
chw.visit.first <- as.integer(df$ancpast_chw_1tri_times)
chw.visit.second <- as.integer(df$ancpast_chw_2tri_times)
chw.visit.third <- as.integer(df$ancpast_chw_3tri_times)
## Concatenate chw provider data.frame
chw <- data.frame(chw, chw.where, chw.home,
chw.gov, chw.private, chw.srhc,
chw.village, chw.eho, chw.dry,
chw.dry.lt15, chw.dry.gteq15lt60,
chw.dry.gteq60lt120, chw.dry.gteq120lt360,
chw.dry.gteq360lt720, chw.dry.gteq720lt1440,
chw.dry.gteq1440, chw.wet,
chw.wet.lt15, chw.wet.gteq15lt60,
chw.wet.gteq60lt120, chw.wet.gteq120lt360,
chw.wet.gteq360lt720, chw.wet.gteq720lt1440,
chw.wet.gteq1440, chw.visit,
chw.visit.first, chw.visit.second,
chw.visit.third)
}
## Return data.frame
return(chw)
}
################################################################################
#
#' Function to recode the ethnic health worker ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded ethnic health worker ANC provider information
#'
#' @examples
#' ## Recode ehw provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_ehw(df = x, status = "current")
#'
#' ## Recode ehw provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_ehw(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_ehw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend ehw
ehw <- as.integer(df$ancnow_who.11)
## Where ehw
ehw.where <- as.integer(df$ancnow_ehw_where)
ehw.home <- bbw::recode(var = ehw.where, recodes = "1=1;NA=NA;else=0")
ehw.gov <- bbw::recode(var = ehw.where, recodes = "2=1;NA=NA;else=0")
ehw.private <- bbw::recode(var = ehw.where, recodes = "3=1;NA=NA;else=0")
ehw.srhc <- bbw::recode(var = ehw.where, recodes = "4=1;NA=NA;else=0")
ehw.village <- bbw::recode(var = ehw.where, recodes = "5=1;NA=NA;else=0")
ehw.eho <- bbw::recode(var = ehw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ehw.dry <- as.integer(df$ancnow_ehw_dist_dry)
ehw.dry.lt15 <- bbw::recode(var = ehw.dry,
recodes = "1=1;NA=NA;else=0")
ehw.dry.gteq15lt60 <- bbw::recode(var = ehw.dry,
recodes = "2=1;NA=NA;else=0")
ehw.dry.gteq60lt120 <- bbw::recode(var = ehw.dry,
recodes = "3=1;NA=NA;else=0")
ehw.dry.gteq120lt360 <- bbw::recode(var = ehw.dry,
recodes = "4=1;NA=NA;else=0")
ehw.dry.gteq360lt720 <- bbw::recode(var = ehw.dry,
recodes = "5=1;NA=NA;else=0")
ehw.dry.gteq720lt1440 <- bbw::recode(var = ehw.dry,
recodes = "6=1;NA=NA;else=0")
ehw.dry.gteq1440 <- bbw::recode(var = ehw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ehw.wet <- as.integer(df$ancnow_ehw_dist_wet)
ehw.wet.lt15 <- bbw::recode(var = ehw.wet,
recodes = "1=1;NA=NA;else=0")
ehw.wet.gteq15lt60 <- bbw::recode(var = ehw.wet,
recodes = "2=1;NA=NA;else=0")
ehw.wet.gteq60lt120 <- bbw::recode(var = ehw.wet,
recodes = "3=1;NA=NA;else=0")
ehw.wet.gteq120lt360 <- bbw::recode(var = ehw.wet,
recodes = "4=1;NA=NA;else=0")
ehw.wet.gteq360lt720 <- bbw::recode(var = ehw.wet,
recodes = "5=1;NA=NA;else=0")
ehw.wet.gteq720lt1440 <- bbw::recode(var = ehw.wet,
recodes = "6=1;NA=NA;else=0")
ehw.wet.gteq1440 <- bbw::recode(var = ehw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ehw.visit <- as.integer(df$ancnow_ehw_visit)
## Number of visits per trimester
ehw.visit.first <- as.integer(df$ancnow_ehw_1tri_times)
ehw.visit.second <- as.integer(df$ancnow_ehw_2tri_times)
ehw.visit.third <- as.integer(df$ancnow_ehw_3tri_times)
## Concatenate ehw provider data.frame
ehw <- data.frame(ehw, ehw.where, ehw.home,
ehw.gov, ehw.private, ehw.srhc,
ehw.village, ehw.eho, ehw.dry,
ehw.dry.lt15, ehw.dry.gteq15lt60,
ehw.dry.gteq60lt120, ehw.dry.gteq120lt360,
ehw.dry.gteq360lt720, ehw.dry.gteq720lt1440,
ehw.dry.gteq1440, ehw.wet,
ehw.wet.lt15, ehw.wet.gteq15lt60,
ehw.wet.gteq60lt120, ehw.wet.gteq120lt360,
ehw.wet.gteq360lt720, ehw.wet.gteq720lt1440,
ehw.wet.gteq1440, ehw.visit,
ehw.visit.first, ehw.visit.second,
ehw.visit.third)
} else {
## Attend ehw
ehw <- as.integer(df$ancpast_who.11)
## Where ehw
ehw.where <- as.integer(df$ancpast_ehw_where)
ehw.home <- bbw::recode(var = ehw.where, recodes = "1=1;NA=NA;else=0")
ehw.gov <- bbw::recode(var = ehw.where, recodes = "2=1;NA=NA;else=0")
ehw.private <- bbw::recode(var = ehw.where, recodes = "3=1;NA=NA;else=0")
ehw.srhc <- bbw::recode(var = ehw.where, recodes = "4=1;NA=NA;else=0")
ehw.village <- bbw::recode(var = ehw.where, recodes = "5=1;NA=NA;else=0")
ehw.eho <- bbw::recode(var = ehw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ehw.dry <- as.integer(df$ancpast_ehw_dist_dry)
ehw.dry.lt15 <- bbw::recode(var = ehw.dry,
recodes = "1=1;NA=NA;else=0")
ehw.dry.gteq15lt60 <- bbw::recode(var = ehw.dry,
recodes = "2=1;NA=NA;else=0")
ehw.dry.gteq60lt120 <- bbw::recode(var = ehw.dry,
recodes = "3=1;NA=NA;else=0")
ehw.dry.gteq120lt360 <- bbw::recode(var = ehw.dry,
recodes = "4=1;NA=NA;else=0")
ehw.dry.gteq360lt720 <- bbw::recode(var = ehw.dry,
recodes = "5=1;NA=NA;else=0")
ehw.dry.gteq720lt1440 <- bbw::recode(var = ehw.dry,
recodes = "6=1;NA=NA;else=0")
ehw.dry.gteq1440 <- bbw::recode(var = ehw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ehw.wet <- as.integer(df$ancpast_ehw_dist_wet)
ehw.wet.lt15 <- bbw::recode(var = ehw.wet,
recodes = "1=1;NA=NA;else=0")
ehw.wet.gteq15lt60 <- bbw::recode(var = ehw.wet,
recodes = "2=1;NA=NA;else=0")
ehw.wet.gteq60lt120 <- bbw::recode(var = ehw.wet,
recodes = "3=1;NA=NA;else=0")
ehw.wet.gteq120lt360 <- bbw::recode(var = ehw.wet,
recodes = "4=1;NA=NA;else=0")
ehw.wet.gteq360lt720 <- bbw::recode(var = ehw.wet,
recodes = "5=1;NA=NA;else=0")
ehw.wet.gteq720lt1440 <- bbw::recode(var = ehw.wet,
recodes = "6=1;NA=NA;else=0")
ehw.wet.gteq1440 <- bbw::recode(var = ehw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ehw.visit <- as.integer(df$ancpast_ehw_visit)
## Number of visits per trimester
ehw.visit.first <- as.integer(df$ancpast_ehw_1tri_times)
ehw.visit.second <- as.integer(df$ancpast_ehw_2tri_times)
ehw.visit.third <- as.integer(df$ancpast_ehw_3tri_times)
## Concatenate ehw provider data.frame
ehw <- data.frame(ehw, ehw.where, ehw.home,
ehw.gov, ehw.private, ehw.srhc,
ehw.village, ehw.eho, ehw.dry,
ehw.dry.lt15, ehw.dry.gteq15lt60,
ehw.dry.gteq60lt120, ehw.dry.gteq120lt360,
ehw.dry.gteq360lt720, ehw.dry.gteq720lt1440,
ehw.dry.gteq1440, ehw.wet,
ehw.wet.lt15, ehw.wet.gteq15lt60,
ehw.wet.gteq60lt120, ehw.wet.gteq120lt360,
ehw.wet.gteq360lt720, ehw.wet.gteq720lt1440,
ehw.wet.gteq1440, ehw.visit,
ehw.visit.first, ehw.visit.second,
ehw.visit.third)
}
## Return data.frame
return(ehw)
}
################################################################################
#
#' Function to recode the personnel type providing antenatal care services for
#' the Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded antenatal care providers visited for
#' antenatal care
#'
#' @examples
#' ## Recode anc provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_provider(df = x, status = "current")
#'
#' ## Recode anc provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_provider(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_provider <- function(df, status = NULL) {
## Specialist
specialist <- recode_provider_specialist(df = df, status = status)
## Doctor
doctor <- recode_provider_doctor(df = df, status = status)
## Nurse
nurse <- recode_provider_nurse(df = df, status = status)
## Health assistant
ha <- recode_provider_ha(df = df, status = status)
## Private doctor
pdoc <- recode_provider_pdoc(df = df, status = status)
## Lady health visitor
lhv <- recode_provider_lhv(df = df, status = status)
## Midwife
midwife <- recode_provider_midwife(df = df, status = status)
## Assistant midwife
amw <- recode_provider_amw(df = df, status = status)
## Traditional birth attendant
tba <- recode_provider_tba(df = df, status = status)
## Community health worker
chw <- recode_provider_chw(df = df, status = status)
## Ethnic health worker
ehw <- recode_provider_ehw(df = df, status = status)
## Determine status
if(status == "current") {
## Provider costs?
incurCost <- as.integer(df$ancnow_cost)
## Amount
amountCost <- as.integer(df$ancnow_amount)
## Item cost: transportation
transportCost <- as.integer(df$ancnow_costitem.1)
transportCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, transportCost)
## Item cost: registration fees
registrationCost <- as.integer(df$ancnow_costitem.2)
registrationCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, registrationCost)
## Item cost: medicines
medicineCost <- as.integer(df$ancnow_costitem.3)
medicineCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, medicineCost)
## Item cost: laboratory fees
labCost <- as.integer(df$ancnow_costitem.4)
labCost <- ifelse(is.na(incurCost) | incurCost == 0, NA, labCost)
## Item cost: provider fees
providerCost <- as.integer(df$ancnow_costitem.5)
providerCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, providerCost)
## Item cost: gifts
giftCost <- as.integer(df$ancnow_costitem.6)
giftCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, giftCost)
## Borrow money?
borrow <- as.integer(df$ancnow_borrow)
} else {
## Provider costs?
incurCost <- as.integer(df$ancpast_cost)
## Amount
amountCost <- as.integer(df$ancpast_amount)
## Item cost: transportation
transportCost <- as.integer(df$ancpast_costitem.1)
transportCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, transportCost)
## Item cost: registration fees
registrationCost <- as.integer(df$ancpast_costitem.2)
registrationCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, registrationCost)
## Item cost: medicines
medicineCost <- as.integer(df$ancpast_costitem.3)
medicineCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, medicineCost)
## Item cost: laboratory fees
labCost <- as.integer(df$ancpast_costitem.4)
labCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, labCost)
## Item cost: provider fees
providerCost <- as.integer(df$ancpast_costitem.5)
providerCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, providerCost)
## Item cost: gifts
giftCost <- as.integer(df$ancpast_costitem.6)
giftCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, giftCost)
## Borrow money?
borrow <- as.integer(df$ancpast_borrow)
}
##
anc1 <- rowSums(cbind(specialist$specialist.visit,
doctor$doctor.visit,
nurse$nurse.visit,
ha$ha.visit,
pdoc$pdoc.visit,
lhv$lhv.visit,
midwife$midwife.visit),
na.rm = TRUE)
anc1 <- bbw::recode(var = anc1,
recodes = "1:hi=1;NA=NA;444=NA;448=NA;888=NA;else=0")
##
anc4 <- rowSums(cbind(specialist$specialist.visit,
doctor$doctor.visit,
nurse$nurse.visit,
ha$ha.visit,
pdoc$pdoc.visit,
lhv$lhv.visit,
midwife$midwife.visit,
amw$amw.visit,
tba$tba.visit,
chw$chw.visit,
ehw$ehw.visit),
na.rm = TRUE)
anc4 <- bbw::recode(var = anc4,
recodes = "4:hi=1;NA=NA;444=NA;448=NA;888=NA;1332=NA;else=0")
## Concatenate provider information to a data.frame
providers <- data.frame(specialist, doctor, nurse, ha, pdoc, lhv,
midwife, amw, tba, chw, ehw, anc1, anc4,
incurCost, amountCost, transportCost, registrationCost,
medicineCost, labCost, providerCost, giftCost, borrow)
## Return data.frame
return(providers)
}
################################################################################
#
#' Function to recode counselling associated with antenatal care for the Myanmar
#' MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded counselling indicators associated with
#' antenatal care
#'
#' @examples
#' ## Recode anc counselling for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_counselling(df = x, status = "current")
#'
#' ## Recode anc counselling for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_counselling(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_counselling <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## MCH book
mchBook <- as.integer(df$ancnow_mchbook)
## Counselling
counsel <- as.integer(df$ancnow_conselling)
## Restrict some foods?
restrict <- as.integer(df$ancnow_restrict)
## Restrict vegetables
restrictVeg <- as.integer(df$ancnow_restrict_item.1)
restrictVeg <- ifelse(is.na(restrict) | restrict == 0, NA, restrictVeg)
## Restrict fruits
restrictFruits <- as.integer(df$ancnow_restrict_item.2)
restrictFruits <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFruits)
## Restrict grains
restrictGrains <- as.integer(df$ancnow_restrict_item.3)
restrictGrains <- ifelse(is.na(restrict) | restrict == 0, NA, restrictGrains)
## Restrict meat
restrictMeat <- as.integer(df$ancnow_restrict_item.4)
restrictMeat <- ifelse(is.na(restrict) | restrict == 0, NA, restrictMeat)
## Restrict fish
restrictFish <- as.integer(df$ancnow_restrict_item.5)
restrictFish <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFish)
## Restrict dairy
restrictDairy <- as.integer(df$ancnow_restrict_item.6)
restrictDairy <- ifelse(is.na(restrict) | restrict == 0, NA, restrictDairy)
## concatenate counselling data.frame
counselling <- data.frame(mchBook, counsel, restrict, restrictVeg,
restrictFruits, restrictGrains, restrictMeat,
restrictFish, restrictDairy)
} else {
## MCH book
mchBook <- as.integer(df$ancpast_mchbook)
## Counselling
counsel <- as.integer(df$ancpast_conselling)
## Restrict some foods?
restrict <- as.integer(df$ancpast_restrict)
## Restrict vegetables
restrictVeg <- as.integer(df$ancpast_restrict_item.1)
restrictVeg <- ifelse(is.na(restrict) | restrict == 0, NA, restrictVeg)
## Restrict fruits
restrictFruits <- as.integer(df$ancpast_restrict_item.2)
restrictFruits <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFruits)
## Restrict grains
restrictGrains <- as.integer(df$ancpast_restrict_item.3)
restrictGrains <- ifelse(is.na(restrict) | restrict == 0, NA, restrictGrains)
## Restrict meat
restrictMeat <- as.integer(df$ancpast_restrict_item.4)
restrictMeat <- ifelse(is.na(restrict) | restrict == 0, NA, restrictMeat)
## Restrict fish
restrictFish <- as.integer(df$ancpast_restrict_item.5)
restrictFish <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFish)
## Restrict dairy
restrictDairy <- as.integer(df$ancpast_restrict_item.6)
restrictDairy <- ifelse(is.na(restrict) | restrict == 0, NA, restrictDairy)
## concatenate counselling data.frame
counselling <- data.frame(mchBook, counsel, restrict, restrictVeg,
restrictFruits, restrictGrains, restrictMeat,
restrictFish, restrictDairy)
}
## Return data.frame
return(counselling)
}
################################################################################
#
#' Function to recode supplementation indicators for antenatal care for the
#' Myanmar MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded supplementation indicators associated with
#' antenatal care
#'
#' @examples
#' ## Recode anc supplementation for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_supplementation(df = x, status = "current")
#'
#' ## Recode anc supplementation for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_supplementation(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_supplementation <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## B1 tablets
b1 <- as.integer(df$ancnow_bone)
b1 <- bbw::recode(var = b1, recodes = "999=0")
## IFA tablets
ifa1 <- as.integer(df$ancnow_rion)
ifa1 <- bbw::recode(var = ifa1, recodes = "999=0")
## IFA - frequency
ifa2 <- as.integer(df$ancnow_iron_freq)
ifa2[ifa2 == 0] <- NA
ifa2[ifa2 == 1 & !is.na(ifa2)] <- (as.integer(df$ancnow_iron_count) * (365 / 12))[ifa2 == 1 & !is.na(ifa2)]
ifa2[ifa2 == 2 & !is.na(ifa2)] <- (as.integer(df$ancnow_iron_count) * ((365/12) / 7))[ifa2 == 2 & !is.na(ifa2)]
ifa2[ifa2 == 3 & !is.na(ifa2)] <- as.integer(df$ancnow_iron_count)[ifa2 == 3 & !is.na(ifa2)]
ifa2 <- floor(ifa2)
ifa2[df$ancnow_rion_length == "1" & !is.na(ifa2)] <- ifa2[df$ancnow_rion_length == "1" & !is.na(ifa2)]
ifa2[df$ancnow_rion_length_oth == "1" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "1" & !is.na(df$ancnow_rion_length_oth)]
ifa2[df$ancnow_rion_length_oth == "2" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "2" & !is.na(df$ancnow_rion_length_oth)] * 2
ifa2[df$ancnow_rion_length_oth == "3" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "3" & !is.na(df$ancnow_rion_length_oth)] * 3
ifa2[df$ancnow_rion_length_oth == "4" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "4" & !is.na(df$ancnow_rion_length_oth)] * 4
ifa2[df$ancnow_rion_length_oth == "5" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "5" & !is.na(df$ancnow_rion_length_oth)] * 5
ifa2[df$ancnow_rion_length_oth == "6" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "6" & !is.na(df$ancnow_rion_length_oth)] * 6
ifa2[df$ancnow_rion_length_oth == "7" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "7" & !is.na(df$ancnow_rion_length_oth)] * 7
ifa2[df$ancnow_rion_length_oth == "8" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "8" & !is.na(df$ancnow_rion_length_oth)] * 8
ifa2[df$ancnow_rion_length_oth == "9" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "9" & !is.na(df$ancnow_rion_length_oth)] * 9
##
ifa3 <- as.integer(df$ancnow_iron_cost)
ifa3 <- ifelse(ifa3 == 1, as.integer(df$ancnow_iron_amount), ifa3)
ifa3 <- bbw::recode(var = ifa3, recodes = "777=NA;999=NA")
## Government hospital
ifa4a <- as.integer(df$ancnow_iron_source.1)
ifa4a <- ifelse(df$ancnow_iron_source == "", NA, ifa4a)
## EHO clinic
ifa4b <- as.integer(df$ancnow_iron_source.2)
ifa4b <- ifelse(df$ancnow_iron_source == "", NA, ifa4b)
## Private doctor/clinic
ifa4c <- as.integer(df$ancnow_iron_source.3)
ifa4c <- ifelse(df$ancnow_iron_source == "", NA, ifa4c)
## SRHC/RHC
ifa4d <- as.integer(df$ancnow_iron_source.4)
ifa4d <- ifelse(df$ancnow_iron_source == "", NA, ifa4d)
## Routine ANC location in ward/village
ifa4e <- as.integer(df$ancnow_iron_source.5)
ifa4e <- ifelse(df$ancnow_iron_source == "", NA, ifa4e)
} else {
## B1 tablets
b1 <- as.integer(df$ancpast_bone)
b1 <- bbw::recode(var = b1, recodes = "999=0")
## IFA tablets
ifa1 <- as.integer(df$ancpast_rion)
ifa1 <- bbw::recode(var = ifa1, recodes = "999=0")
## IFA - frequency
ifa2 <- as.integer(df$ancpast_iron_freq)
ifa2a <- as.integer(df$ancpast_iron_count)
ifa2a <- bbw::recode(var = ifa2a, recodes = "45:hi=NA")
ifa2[ifa2 == 0] <- NA
ifa2[ifa2 == 1 & !is.na(ifa2)] <- (ifa2a * (365.25 / 12))[ifa2 == 1 & !is.na(ifa2)]
ifa2[ifa2 == 2 & !is.na(ifa2)] <- (ifa2a * ((365.25 / 12) / 7))[ifa2 == 2 & !is.na(ifa2)]
ifa2[ifa2 == 3 & !is.na(ifa2)] <- ifa2a[ifa2 == 3 & !is.na(ifa2)]
ifa2 <- floor(ifa2)
ifa2[df$ancpast_rion_length == "1" & !is.na(ifa2)] <- ifa2[df$ancpast_rion_length == "1" & !is.na(ifa2)]
ifa2[df$ancpast_rion_length_oth == "1" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "1" & !is.na(df$ancpast_rion_length_oth)]
ifa2[df$ancpast_rion_length_oth == "2" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "2" & !is.na(df$ancpast_rion_length_oth)] * 2
ifa2[df$ancpast_rion_length_oth == "3" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "3" & !is.na(df$ancpast_rion_length_oth)] * 3
ifa2[df$ancpast_rion_length_oth == "4" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "4" & !is.na(df$ancpast_rion_length_oth)] * 4
ifa2[df$ancpast_rion_length_oth == "5" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "5" & !is.na(df$ancpast_rion_length_oth)] * 5
ifa2[df$ancpast_rion_length_oth == "6" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "6" & !is.na(df$ancpast_rion_length_oth)] * 6
ifa2[df$ancpast_rion_length_oth == "7" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "7" & !is.na(df$ancpast_rion_length_oth)] * 7
ifa2[df$ancpast_rion_length_oth == "8" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "8" & !is.na(df$ancpast_rion_length_oth)] * 8
ifa2[df$ancpast_rion_length_oth == "9" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "9" & !is.na(df$ancpast_rion_length_oth)] * 9
##
ifa3 <- as.integer(df$ancpast_iron_cost)
ifa3 <- ifelse(ifa3 == 1, as.integer(df$ancpast_iron_amount), ifa3)
ifa3 <- bbw::recode(var = ifa3, recodes = "444=NA;777=NA;999=NA")
## Government hospital
ifa4a <- as.integer(df$ancpast_iron_source.1)
ifa4a <- ifelse(df$ancpast_iron_source == "", NA, ifa4a)
## EHO clinic
ifa4b <- as.integer(df$ancpast_iron_source.2)
ifa4b <- ifelse(df$ancpast_iron_source == "", NA, ifa4b)
## Private doctor/clinic
ifa4c <- as.integer(df$ancpast_iron_source.3)
ifa4c <- ifelse(df$ancpast_iron_source == "", NA, ifa4c)
## SRHC/RHC
ifa4d <- as.integer(df$ancpast_iron_source.4)
ifa4d <- ifelse(df$ancpast_iron_source == "", NA, ifa4d)
## Routine ANC location in ward/village
ifa4e <- as.integer(df$ancpast_iron_source.5)
ifa4e <- ifelse(df$ancpast_iron_source == "", NA, ifa4e)
}
## concatenate
ancSupp <- data.frame(b1, ifa1, ifa2, ifa3, ifa4a, ifa4b, ifa4c, ifa4d, ifa4e)
## Return
return(ancSupp)
}
################################################################################
#
#' Function to recode testing for infections indicators for antenatal care for
#' the Myanmar MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded testing for infections associated with
#' antenatal care
#'
#' @examples
#' ## Recode data for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_testing(df = x, status = "current")
#'
#' ## Recode data for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_testing(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_testing <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Tests done
test1 <- suppressWarnings(as.integer(df$ancnow_test_yesno))
test1 <- bbw::recode(var = test1, recodes = "1:4=1;888=1;0=0;999=0;NA=NA")
## Hepatitis B
test2a <- suppressWarnings(as.integer(df$ancnow_test_yesno.1))
test2a <- ifelse(is.na(test1), NA, test2a)
## Hepatitis C
test2b <- suppressWarnings(as.integer(df$ancnow_test_yesno.2))
test2b <- ifelse(is.na(test1), NA, test2b)
## HIV/AIDS
test2c <- suppressWarnings(as.integer(df$ancnow_test_yesno.3))
test2c <- ifelse(is.na(test1), NA, test2c)
## Syphillis
test2d <- suppressWarnings(as.integer(df$ancnow_test_yesno.4))
test2d <- ifelse(is.na(test1), NA, test2d)
## Code for other tests
## Government hospital
test3a <- suppressWarnings(as.integer(df$ancnow_test_where.1))
test3a <- ifelse(is.na(test1), NA, test3a)
## EHO clinic
test3b <- suppressWarnings(as.integer(df$ancnow_test_where.2))
test3b <- ifelse(is.na(test1), NA, test3b)
## Private doctor/clinic
test3c <- suppressWarnings(as.integer(df$ancnow_test_where.3))
test3c <- ifelse(is.na(test1), NA, test3c)
## SRHC/RHC
test3d <- suppressWarnings(as.integer(df$ancnow_test_where.4))
test3d <- ifelse(is.na(test1), NA, test3d)
## Routine ANC location in ward/village
test3e <- suppressWarnings(as.integer(df$ancnow_test_where.5))
test3e <- ifelse(is.na(test1), NA, test3e)
## Code for other locations
## Does test cost?
test4 <- suppressWarnings(as.integer(df$ancnow_test_cost))
test5 <- test4
test4 <- bbw::recode(var = test4, recodes = "1:hi=1;0=0;NA=NA")
} else {
## Tests done
test1 <- suppressWarnings(as.integer(df$ancpast_test_yesno))
test1 <- bbw::recode(var = test1, recodes = "1:4=1;888=1;0=0;999=0;NA=NA")
## Hepatitis B
test2a <- suppressWarnings(as.integer(df$ancpast_test_yesno.1))
test2a <- ifelse(is.na(test1), NA, test2a)
## Hepatitis C
test2b <- suppressWarnings(as.integer(df$ancpast_test_yesno.2))
test2b <- ifelse(is.na(test1), NA, test2b)
## HIV/AIDS
test2c <- suppressWarnings(as.integer(df$ancpast_test_yesno.3))
test2c <- ifelse(is.na(test1), NA, test2c)
## Syphillis
test2d <- suppressWarnings(as.integer(df$ancpast_test_yesno.4))
test2d <- ifelse(is.na(test1), NA, test2d)
## Code for other tests
## Government hospital
test3a <- suppressWarnings(as.integer(df$ancpast_test_where.1))
test3a <- ifelse(is.na(test1), NA, test3a)
## EHO clinic
test3b <- suppressWarnings(as.integer(df$ancpast_test_where.2))
test3b <- ifelse(is.na(test1), NA, test3b)
## Private doctor/clinic
test3c <- suppressWarnings(as.integer(df$ancpast_test_where.3))
test3c <- ifelse(is.na(test1), NA, test3c)
## SRHC/RHC
test3d <- suppressWarnings(as.integer(df$ancpast_test_where.4))
test3d <- ifelse(is.na(test1), NA, test3d)
## Routine ANC location in ward/village
test3e <- suppressWarnings(as.integer(df$ancpast_test_where.5))
test3e <- ifelse(is.na(test1), NA, test3e)
## Code for other locations
## Does test cost?
test4 <- suppressWarnings(as.integer(df$ancpast_test_cost))
test5 <- test4
test4 <- bbw::recode(var = test4, recodes = "1:hi=1;0=0;NA=NA")
}
## Concatenate testing indicators
test <- data.frame(test1, test2a, test2b, test2c, test2d,
test3a, test3b, test3c, test3d, test3e,
test4, test5)
## Return
return(test)
}
################################################################################
#
#' Function to recode antenatal care indicators for the Myanmar MCCT Programme
#' Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#' @param core.columns A vector of variable names to include in resulting
#'
#' @return A data.frame of recoded antenatal care indicators
#'
#' @examples
#' ## Recode anc indicators for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc(df = x, status = "current")
#'
#' ## Recode anc indicators for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc(df = x, status = "past")
#'
#' @export
#
################################################################################
recode_anc <- function(df,
status = NULL,
core.columns = c("KEY",
"geo_rural",
"geo_state",
"geo_villward",
"sample_component")) {
## Provider
provider <- recode_anc_provider(df = df, status = status)
## Counselling
counselling <- recode_anc_counselling(df = df, status = status)
## Supplementation
supplementation <- recode_anc_supplementation(df = df, status = status)
## Testing
testing <- recode_anc_testing(df = df, status = status)
## Concatenate all ANC indicators
ancDF <- data.frame(df[ , core.columns], provider,
counselling, supplementation, testing)
##
return(ancDF)
}
validmeasures/myanmarMCCTdata documentation built on March 29, 2020, 10:27 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions create_anc recode_provider_specialist recode_provider_doctor recode_provider_nurse recode_provider_ha recode_provider_pdoc recode_provider_lhv recode_provider_midwife recode_provider_amw recode_provider_tba recode_provider_chw recode_provider_ehw recode_anc_provider recode_anc_counselling recode_anc_supplementation recode_anc_testing recode_anc
Documented in create_anc recode_anc recode_anc_counselling recode_anc_provider recode_anc_supplementation recode_anc_testing recode_provider_amw recode_provider_chw recode_provider_doctor recode_provider_ehw recode_provider_ha recode_provider_lhv recode_provider_midwife recode_provider_nurse recode_provider_pdoc recode_provider_specialist recode_provider_tba
################################################################################
#
#' Function to create raw ANC dataset
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing ANC data
#' @param x A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing household information that will be linked to the
#' ANC data
#' @param y A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing household roster information that will be linked to the
#' ANC data
#' @param status A character value indicating whether to create data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame containing raw ANC data for the Myanmar MCCT Programme
#' Evaluation Study
#'
#' @examples
#' create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#'
#' @export
#'
#
################################################################################
create_anc <- function(df, x, y, status) {
## Create data.frame from hh dataset to get needed information
x <- x[ , c("KEY", "intrv_date", "geo_state", "geo_rural", "geo_villward",
"sample_component", "will_participate")]
## Create data.frame from hhMembers dataset to get needed information
y <- y[ , c("PARENT_KEY", "KEY", "hh_mem_sex", "hh_mem_age",
"hh_mem_age_month", "hh_mem_dob", "hh_mem_pregnow",
"hh_mem_u5num", "hh_mem_highedu", "hh_mem_occup")]
if(status == "current") {
## change KEY to match anc1 KEY
y$KEY <- stringr::str_replace_all(string = y$KEY,
pattern = "grp_hh",
replacement = "ancnow_rep")
}
if(status == "past") {
## change KEY to match anc2 KEY
y$KEY <- stringr::str_replace_all(string = y$KEY,
pattern = "grp_hh",
replacement = "ancpast_rep")
}
## Merge hhMembers data with childHealth to get hhMember information
xy <- merge(y, df, by.x = "KEY", by.y = "KEY", all.y = TRUE)
## Merge hh data with merged childHealth data to get hh information
z <- merge(x, xy, by.x = "KEY", by.y = "PARENT_KEY.y", all.y = TRUE)
## Calculate age in days
age <- floor(as.numeric(lubridate::mdy(z$intrv_date) -
lubridate::mdy(z$hh_mem_dob)) / 365.25)
age <- ifelse(is.na(age),
floor(sum(as.integer(z$hh_mem_age),
(as.integer(z$hh_mem_age_month) / 12),
na.rm = TRUE)),
age)
## Add age to data.frame
z$age <- age
if(status == "current") {
z <- z[as.integer(z$hh_mem_pregnow) == 1 & !is.na(z$hh_mem_pregnow), ]
}
if(status == "past") {
z <- z[as.integer(z$hh_mem_pregnow) == 0 &
!is.na(z$hh_mem_pregnow) &
as.integer(z$hh_mem_u5num) > 0 & !is.na(z$hh_mem_u5num), ]
}
## remove unnecessary variables
z <- z[ , names(z)[!names(z) %in% c("KEY.y",
"PARENT_KEY.x",
"SET.OF.ancnow_rep",
"SET.OF.ancpast_rep")]]
## return data.frame
return(z)
}
################################################################################
#
#' Function to recode the specialist ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded specialist ANC provider information
#'
#' @examples
#' ## Recode specialist provider for current pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_specialist(df = x, status = "current")
#'
#' ## Recode specialist provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_specialist(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_specialist <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend specialist
specialist <- as.integer(df$ancnow_who.1)
## Where specialist
specialist.where <- as.integer(df$ancnow_pdoc_where)
specialist.home <- bbw::recode(var = specialist.where,
recodes = "1=1;NA=NA;else=0")
specialist.gov <- bbw::recode(var = specialist.where,
recodes = "2=1;NA=NA;else=0")
specialist.private <- bbw::recode(var = specialist.where,
recodes = "3=1;NA=NA;else=0")
specialist.srhc <- bbw::recode(var = specialist.where,
recodes = "4=1;NA=NA;else=0")
specialist.village <- bbw::recode(var = specialist.where,
recodes = "5=1;NA=NA;else=0")
specialist.eho <- bbw::recode(var = specialist.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
specialist.dry <- as.integer(df$ancnow_pdoc_dist_dry)
specialist.dry.lt15 <- bbw::recode(var = specialist.dry,
recodes = "1=1;NA=NA;else=0")
specialist.dry.gteq15lt60 <- bbw::recode(var = specialist.dry,
recodes = "2=1;NA=NA;else=0")
specialist.dry.gteq60lt120 <- bbw::recode(var = specialist.dry,
recodes = "3=1;NA=NA;else=0")
specialist.dry.gteq120lt360 <- bbw::recode(var = specialist.dry,
recodes = "4=1;NA=NA;else=0")
specialist.dry.gteq360lt720 <- bbw::recode(var = specialist.dry,
recodes = "5=1;NA=NA;else=0")
specialist.dry.gteq720lt1440 <- bbw::recode(var = specialist.dry,
recodes = "6=1;NA=NA;else=0")
specialist.dry.gteq1440 <- bbw::recode(var = specialist.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
specialist.wet <- as.integer(df$ancnow_pdoc_dist_wet)
specialist.wet.lt15 <- bbw::recode(var = specialist.wet,
recodes = "1=1;NA=NA;else=0")
specialist.wet.gteq15lt60 <- bbw::recode(var = specialist.wet,
recodes = "2=1;NA=NA;else=0")
specialist.wet.gteq60lt120 <- bbw::recode(var = specialist.wet,
recodes = "3=1;NA=NA;else=0")
specialist.wet.gteq120lt360 <- bbw::recode(var = specialist.wet,
recodes = "4=1;NA=NA;else=0")
specialist.wet.gteq360lt720 <- bbw::recode(var = specialist.wet,
recodes = "5=1;NA=NA;else=0")
specialist.wet.gteq720lt1440 <- bbw::recode(var = specialist.wet,
recodes = "6=1;NA=NA;else=0")
specialist.wet.gteq1440 <- bbw::recode(var = specialist.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
specialist.visit <- as.integer(df$ancnow_pdoc_visit)
## Number of visits per trimester
specialist.visit.first <- as.integer(df$ancnow_pdoc_1tri_times)
specialist.visit.second <- as.integer(df$ancnow_pdoc_2tri_times)
specialist.visit.third <- as.integer(df$ancnow_pdoc_3tri_times)
## Concatenate specialist provider data.frame
specialist <- data.frame(specialist, specialist.where, specialist.home,
specialist.gov, specialist.private, specialist.srhc,
specialist.village, specialist.eho, specialist.dry,
specialist.dry.lt15, specialist.dry.gteq15lt60,
specialist.dry.gteq60lt120,
specialist.dry.gteq120lt360,
specialist.dry.gteq360lt720,
specialist.dry.gteq720lt1440,
specialist.dry.gteq1440, specialist.wet,
specialist.wet.lt15, specialist.wet.gteq15lt60,
specialist.wet.gteq60lt120,
specialist.wet.gteq120lt360,
specialist.wet.gteq360lt720,
specialist.wet.gteq720lt1440,
specialist.wet.gteq1440, specialist.visit,
specialist.visit.first, specialist.visit.second,
specialist.visit.third)
} else {
## Attend specialist
specialist <- as.integer(df$ancpast_who.1)
## Where specialist
specialist.where <- as.integer(df$ancpast_pdoc_where)
specialist.home <- bbw::recode(var = specialist.where,
recodes = "1=1;NA=NA;else=0")
specialist.gov <- bbw::recode(var = specialist.where,
recodes = "2=1;NA=NA;else=0")
specialist.private <- bbw::recode(var = specialist.where,
recodes = "3=1;NA=NA;else=0")
specialist.srhc <- bbw::recode(var = specialist.where,
recodes = "4=1;NA=NA;else=0")
specialist.village <- bbw::recode(var = specialist.where,
recodes = "5=1;NA=NA;else=0")
specialist.eho <- bbw::recode(var = specialist.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
specialist.dry <- as.integer(df$ancpast_pdoc_dist_dry)
specialist.dry.lt15 <- bbw::recode(var = specialist.dry,
recodes = "1=1;NA=NA;else=0")
specialist.dry.gteq15lt60 <- bbw::recode(var = specialist.dry,
recodes = "2=1;NA=NA;else=0")
specialist.dry.gteq60lt120 <- bbw::recode(var = specialist.dry,
recodes = "3=1;NA=NA;else=0")
specialist.dry.gteq120lt360 <- bbw::recode(var = specialist.dry,
recodes = "4=1;NA=NA;else=0")
specialist.dry.gteq360lt720 <- bbw::recode(var = specialist.dry,
recodes = "5=1;NA=NA;else=0")
specialist.dry.gteq720lt1440 <- bbw::recode(var = specialist.dry,
recodes = "6=1;NA=NA;else=0")
specialist.dry.gteq1440 <- bbw::recode(var = specialist.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
specialist.wet <- as.integer(df$ancpast_pdoc_dist_wet)
specialist.wet.lt15 <- bbw::recode(var = specialist.wet,
recodes = "1=1;NA=NA;else=0")
specialist.wet.gteq15lt60 <- bbw::recode(var = specialist.wet,
recodes = "2=1;NA=NA;else=0")
specialist.wet.gteq60lt120 <- bbw::recode(var = specialist.wet,
recodes = "3=1;NA=NA;else=0")
specialist.wet.gteq120lt360 <- bbw::recode(var = specialist.wet,
recodes = "4=1;NA=NA;else=0")
specialist.wet.gteq360lt720 <- bbw::recode(var = specialist.wet,
recodes = "5=1;NA=NA;else=0")
specialist.wet.gteq720lt1440 <- bbw::recode(var = specialist.wet,
recodes = "6=1;NA=NA;else=0")
specialist.wet.gteq1440 <- bbw::recode(var = specialist.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
specialist.visit <- as.integer(df$ancpast_pdoc_visit)
## Number of visits per trimester
specialist.visit.first <- as.integer(df$ancpast_pdoc_1tri_times)
specialist.visit.second <- as.integer(df$ancpast_pdoc_2tri_times)
specialist.visit.third <- as.integer(df$ancpast_pdoc_3tri_times)
## Concatenate specialist provider data.frame
specialist <- data.frame(specialist, specialist.where, specialist.home,
specialist.gov,
specialist.private, specialist.srhc,
specialist.village,
specialist.eho, specialist.dry,
specialist.dry.lt15, specialist.dry.gteq15lt60,
specialist.dry.gteq60lt120,
specialist.dry.gteq120lt360,
specialist.dry.gteq360lt720,
specialist.dry.gteq720lt1440,
specialist.dry.gteq1440, specialist.wet,
specialist.wet.lt15, specialist.wet.gteq15lt60,
specialist.wet.gteq60lt120,
specialist.wet.gteq120lt360,
specialist.wet.gteq360lt720,
specialist.wet.gteq720lt1440,
specialist.wet.gteq1440, specialist.visit,
specialist.visit.first, specialist.visit.second,
specialist.visit.third)
}
## Return data.frame
return(specialist)
}
################################################################################
#
#' Function to recode the doctor ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded doctor ANC provider information
#'
#' @examples
#' ## Recode provider doctor for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_doctor(df = x, status = "current")
#'
#' ## Recode provider doctor for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_doctor(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_doctor <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend doctor
doctor <- as.integer(df$ancnow_who.2)
## Where doctor
doctor.where <- as.integer(df$ancnow_doc_where)
doctor.home <- bbw::recode(var = doctor.where,
recodes = "1=1;NA=NA;else=0")
doctor.gov <- bbw::recode(var = doctor.where,
recodes = "2=1;NA=NA;else=0")
doctor.private <- bbw::recode(var = doctor.where,
recodes = "3=1;NA=NA;else=0")
doctor.srhc <- bbw::recode(var = doctor.where,
recodes = "4=1;NA=NA;else=0")
doctor.village <- bbw::recode(var = doctor.where,
recodes = "5=1;NA=NA;else=0")
doctor.eho <- bbw::recode(var = doctor.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
doctor.dry <- as.integer(df$ancnow_doc_dist_dry)
doctor.dry.lt15 <- bbw::recode(var = doctor.dry,
recodes = "1=1;NA=NA;else=0")
doctor.dry.gteq15lt60 <- bbw::recode(var = doctor.dry,
recodes = "2=1;NA=NA;else=0")
doctor.dry.gteq60lt120 <- bbw::recode(var = doctor.dry,
recodes = "3=1;NA=NA;else=0")
doctor.dry.gteq120lt360 <- bbw::recode(var = doctor.dry,
recodes = "4=1;NA=NA;else=0")
doctor.dry.gteq360lt720 <- bbw::recode(var = doctor.dry,
recodes = "5=1;NA=NA;else=0")
doctor.dry.gteq720lt1440 <- bbw::recode(var = doctor.dry,
recodes = "6=1;NA=NA;else=0")
doctor.dry.gteq1440 <- bbw::recode(var = doctor.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
doctor.wet <- as.integer(df$ancnow_doc_dist_wet)
doctor.wet.lt15 <- bbw::recode(var = doctor.wet,
recodes = "1=1;NA=NA;else=0")
doctor.wet.gteq15lt60 <- bbw::recode(var = doctor.wet,
recodes = "2=1;NA=NA;else=0")
doctor.wet.gteq60lt120 <- bbw::recode(var = doctor.wet,
recodes = "3=1;NA=NA;else=0")
doctor.wet.gteq120lt360 <- bbw::recode(var = doctor.wet,
recodes = "4=1;NA=NA;else=0")
doctor.wet.gteq360lt720 <- bbw::recode(var = doctor.wet,
recodes = "5=1;NA=NA;else=0")
doctor.wet.gteq720lt1440 <- bbw::recode(var = doctor.wet,
recodes = "6=1;NA=NA;else=0")
doctor.wet.gteq1440 <- bbw::recode(var = doctor.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
doctor.visit <- as.integer(df$ancnow_doc_visit)
## Number of visits per trimester
doctor.visit.first <- as.integer(df$ancnow_doc_1tri_times)
doctor.visit.second <- as.integer(df$ancnow_doc_2tri_times)
doctor.visit.third <- as.integer(df$ancnow_doc_3tri_times)
## Concatenate doctor provider data.frame
doctor <- data.frame(doctor, doctor.where, doctor.home,
doctor.gov, doctor.private, doctor.srhc,
doctor.village, doctor.eho, doctor.dry,
doctor.dry.lt15, doctor.dry.gteq15lt60,
doctor.dry.gteq60lt120, doctor.dry.gteq120lt360,
doctor.dry.gteq360lt720, doctor.dry.gteq720lt1440,
doctor.dry.gteq1440, doctor.wet,
doctor.wet.lt15, doctor.wet.gteq15lt60,
doctor.wet.gteq60lt120, doctor.wet.gteq120lt360,
doctor.wet.gteq360lt720, doctor.wet.gteq720lt1440,
doctor.wet.gteq1440, doctor.visit,
doctor.visit.first, doctor.visit.second,
doctor.visit.third)
} else {
## Attend doctor
doctor <- as.integer(df$ancpast_who.2)
## Where doctor
doctor.where <- as.integer(df$ancpast_doc_where)
doctor.home <- bbw::recode(var = doctor.where,
recodes = "1=1;NA=NA;else=0")
doctor.gov <- bbw::recode(var = doctor.where,
recodes = "2=1;NA=NA;else=0")
doctor.private <- bbw::recode(var = doctor.where,
recodes = "3=1;NA=NA;else=0")
doctor.srhc <- bbw::recode(var = doctor.where,
recodes = "4=1;NA=NA;else=0")
doctor.village <- bbw::recode(var = doctor.where,
recodes = "5=1;NA=NA;else=0")
doctor.eho <- bbw::recode(var = doctor.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
doctor.dry <- as.integer(df$ancpast_doc_dist_dry)
doctor.dry.lt15 <- bbw::recode(var = doctor.dry,
recodes = "1=1;NA=NA;else=0")
doctor.dry.gteq15lt60 <- bbw::recode(var = doctor.dry,
recodes = "2=1;NA=NA;else=0")
doctor.dry.gteq60lt120 <- bbw::recode(var = doctor.dry,
recodes = "3=1;NA=NA;else=0")
doctor.dry.gteq120lt360 <- bbw::recode(var = doctor.dry,
recodes = "4=1;NA=NA;else=0")
doctor.dry.gteq360lt720 <- bbw::recode(var = doctor.dry,
recodes = "5=1;NA=NA;else=0")
doctor.dry.gteq720lt1440 <- bbw::recode(var = doctor.dry,
recodes = "6=1;NA=NA;else=0")
doctor.dry.gteq1440 <- bbw::recode(var = doctor.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
doctor.wet <- as.integer(df$ancpast_doc_dist_wet)
doctor.wet.lt15 <- bbw::recode(var = doctor.wet,
recodes = "1=1;NA=NA;else=0")
doctor.wet.gteq15lt60 <- bbw::recode(var = doctor.wet,
recodes = "2=1;NA=NA;else=0")
doctor.wet.gteq60lt120 <- bbw::recode(var = doctor.wet,
recodes = "3=1;NA=NA;else=0")
doctor.wet.gteq120lt360 <- bbw::recode(var = doctor.wet,
recodes = "4=1;NA=NA;else=0")
doctor.wet.gteq360lt720 <- bbw::recode(var = doctor.wet,
recodes = "5=1;NA=NA;else=0")
doctor.wet.gteq720lt1440 <- bbw::recode(var = doctor.wet,
recodes = "6=1;NA=NA;else=0")
doctor.wet.gteq1440 <- bbw::recode(var = doctor.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
doctor.visit <- as.integer(df$ancpast_doc_visit)
## Number of visits per trimester
doctor.visit.first <- as.integer(df$ancpast_doc_1tri_times)
doctor.visit.second <- as.integer(df$ancpast_doc_2tri_times)
doctor.visit.third <- as.integer(df$ancpast_doc_3tri_times)
## Concatenate doctor provider data.frame
doctor <- data.frame(doctor, doctor.where, doctor.home,
doctor.gov, doctor.private, doctor.srhc,
doctor.village, doctor.eho, doctor.dry,
doctor.dry.lt15, doctor.dry.gteq15lt60,
doctor.dry.gteq60lt120, doctor.dry.gteq120lt360,
doctor.dry.gteq360lt720, doctor.dry.gteq720lt1440,
doctor.dry.gteq1440, doctor.wet,
doctor.wet.lt15, doctor.wet.gteq15lt60,
doctor.wet.gteq60lt120, doctor.wet.gteq120lt360,
doctor.wet.gteq360lt720, doctor.wet.gteq720lt1440,
doctor.wet.gteq1440, doctor.visit,
doctor.visit.first, doctor.visit.second,
doctor.visit.third)
}
## Return data.frame
return(doctor)
}
################################################################################
#
#' Function to recode the nurse ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded nurse ANC provider information
#'
#' @examples
#' ## Recode nurse provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_nurse(df = x, status = "current")
#'
#' ## Recode nurse provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_nurse(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_nurse <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend nurse
nurse <- as.integer(df$ancnow_who.3)
## Where nurse
nurse.where <- as.integer(df$ancnow_nurs_where)
nurse.home <- bbw::recode(var = nurse.where,
recodes = "1=1;NA=NA;else=0")
nurse.gov <- bbw::recode(var = nurse.where,
recodes = "2=1;NA=NA;else=0")
nurse.private <- bbw::recode(var = nurse.where,
recodes = "3=1;NA=NA;else=0")
nurse.srhc <- bbw::recode(var = nurse.where,
recodes = "4=1;NA=NA;else=0")
nurse.village <- bbw::recode(var = nurse.where,
recodes = "5=1;NA=NA;else=0")
nurse.eho <- bbw::recode(var = nurse.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
nurse.dry <- as.integer(df$ancnow_nurs_dist_dry)
nurse.dry.lt15 <- bbw::recode(var = nurse.dry,
recodes = "1=1;NA=NA;else=0")
nurse.dry.gteq15lt60 <- bbw::recode(var = nurse.dry,
recodes = "2=1;NA=NA;else=0")
nurse.dry.gteq60lt120 <- bbw::recode(var = nurse.dry,
recodes = "3=1;NA=NA;else=0")
nurse.dry.gteq120lt360 <- bbw::recode(var = nurse.dry,
recodes = "4=1;NA=NA;else=0")
nurse.dry.gteq360lt720 <- bbw::recode(var = nurse.dry,
recodes = "5=1;NA=NA;else=0")
nurse.dry.gteq720lt1440 <- bbw::recode(var = nurse.dry,
recodes = "6=1;NA=NA;else=0")
nurse.dry.gteq1440 <- bbw::recode(var = nurse.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
nurse.wet <- as.integer(df$ancnow_nurs_dist_wet)
nurse.wet.lt15 <- bbw::recode(var = nurse.wet,
recodes = "1=1;NA=NA;else=0")
nurse.wet.gteq15lt60 <- bbw::recode(var = nurse.wet,
recodes = "2=1;NA=NA;else=0")
nurse.wet.gteq60lt120 <- bbw::recode(var = nurse.wet,
recodes = "3=1;NA=NA;else=0")
nurse.wet.gteq120lt360 <- bbw::recode(var = nurse.wet,
recodes = "4=1;NA=NA;else=0")
nurse.wet.gteq360lt720 <- bbw::recode(var = nurse.wet,
recodes = "5=1;NA=NA;else=0")
nurse.wet.gteq720lt1440 <- bbw::recode(var = nurse.wet,
recodes = "6=1;NA=NA;else=0")
nurse.wet.gteq1440 <- bbw::recode(var = nurse.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
nurse.visit <- as.integer(df$ancnow_nurs_visit)
## Number of visits per trimester
nurse.visit.first <- as.integer(df$ancnow_nurs_1tri_times)
nurse.visit.second <- as.integer(df$ancnow_nurs_2tri_times)
nurse.visit.third <- as.integer(df$ancnow_nurs_3tri_times)
## Concatenate nurse provider data.frame
nurse <- data.frame(nurse, nurse.where, nurse.home,
nurse.gov, nurse.private, nurse.srhc,
nurse.village, nurse.eho, nurse.dry,
nurse.dry.lt15, nurse.dry.gteq15lt60,
nurse.dry.gteq60lt120, nurse.dry.gteq120lt360,
nurse.dry.gteq360lt720, nurse.dry.gteq720lt1440,
nurse.dry.gteq1440, nurse.wet,
nurse.wet.lt15, nurse.wet.gteq15lt60,
nurse.wet.gteq60lt120, nurse.wet.gteq120lt360,
nurse.wet.gteq360lt720, nurse.wet.gteq720lt1440,
nurse.wet.gteq1440, nurse.visit,
nurse.visit.first, nurse.visit.second,
nurse.visit.third)
} else {
## Attend nurse
nurse <- as.integer(df$ancpast_who.3)
## Where nurse
nurse.where <- as.integer(df$ancpast_nurs_where)
nurse.home <- bbw::recode(var = nurse.where,
recodes = "1=1;NA=NA;else=0")
nurse.gov <- bbw::recode(var = nurse.where,
recodes = "2=1;NA=NA;else=0")
nurse.private <- bbw::recode(var = nurse.where,
recodes = "3=1;NA=NA;else=0")
nurse.srhc <- bbw::recode(var = nurse.where,
recodes = "4=1;NA=NA;else=0")
nurse.village <- bbw::recode(var = nurse.where,
recodes = "5=1;NA=NA;else=0")
nurse.eho <- bbw::recode(var = nurse.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
nurse.dry <- as.integer(df$ancpast_nurs_dist_dry)
nurse.dry.lt15 <- bbw::recode(var = nurse.dry,
recodes = "1=1;NA=NA;else=0")
nurse.dry.gteq15lt60 <- bbw::recode(var = nurse.dry,
recodes = "2=1;NA=NA;else=0")
nurse.dry.gteq60lt120 <- bbw::recode(var = nurse.dry,
recodes = "3=1;NA=NA;else=0")
nurse.dry.gteq120lt360 <- bbw::recode(var = nurse.dry,
recodes = "4=1;NA=NA;else=0")
nurse.dry.gteq360lt720 <- bbw::recode(var = nurse.dry,
recodes = "5=1;NA=NA;else=0")
nurse.dry.gteq720lt1440 <- bbw::recode(var = nurse.dry,
recodes = "6=1;NA=NA;else=0")
nurse.dry.gteq1440 <- bbw::recode(var = nurse.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
nurse.wet <- as.integer(df$ancpast_nurs_dist_wet)
nurse.wet.lt15 <- bbw::recode(var = nurse.wet,
recodes = "1=1;NA=NA;else=0")
nurse.wet.gteq15lt60 <- bbw::recode(var = nurse.wet,
recodes = "2=1;NA=NA;else=0")
nurse.wet.gteq60lt120 <- bbw::recode(var = nurse.wet,
recodes = "3=1;NA=NA;else=0")
nurse.wet.gteq120lt360 <- bbw::recode(var = nurse.wet,
recodes = "4=1;NA=NA;else=0")
nurse.wet.gteq360lt720 <- bbw::recode(var = nurse.wet,
recodes = "5=1;NA=NA;else=0")
nurse.wet.gteq720lt1440 <- bbw::recode(var = nurse.wet,
recodes = "6=1;NA=NA;else=0")
nurse.wet.gteq1440 <- bbw::recode(var = nurse.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
nurse.visit <- as.integer(df$ancpast_nurs_visit)
## Number of visits per trimester
nurse.visit.first <- as.integer(df$ancpast_nurs_1tri_times)
nurse.visit.second <- as.integer(df$ancpast_nurs_2tri_times)
nurse.visit.third <- as.integer(df$ancpast_nurs_3tri_times)
## Concatenate nurse provider data.frame
nurse <- data.frame(nurse, nurse.where, nurse.home,
nurse.gov, nurse.private, nurse.srhc,
nurse.village, nurse.eho, nurse.dry,
nurse.dry.lt15, nurse.dry.gteq15lt60,
nurse.dry.gteq60lt120, nurse.dry.gteq120lt360,
nurse.dry.gteq360lt720, nurse.dry.gteq720lt1440,
nurse.dry.gteq1440, nurse.wet,
nurse.wet.lt15, nurse.wet.gteq15lt60,
nurse.wet.gteq60lt120, nurse.wet.gteq120lt360,
nurse.wet.gteq360lt720, nurse.wet.gteq720lt1440,
nurse.wet.gteq1440, nurse.visit,
nurse.visit.first, nurse.visit.second,
nurse.visit.third)
}
## Return data.frame
return(nurse)
}
################################################################################
#
#' Function to recode the health assistant ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded health assistant ANC provider information
#'
#' @examples
#' ## Recode health assistant provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_ha(df = x, status = "current")
#'
#' ## Recode health assistant provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_ha(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_ha <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend ha
ha <- as.integer(df$ancnow_who.4)
## Where ha
ha.where <- as.integer(df$ancnow_ha_where)
ha.home <- bbw::recode(var = ha.where,
recodes = "1=1;NA=NA;else=0")
ha.gov <- bbw::recode(var = ha.where,
recodes = "2=1;NA=NA;else=0")
ha.private <- bbw::recode(var = ha.where,
recodes = "3=1;NA=NA;else=0")
ha.srhc <- bbw::recode(var = ha.where,
recodes = "4=1;NA=NA;else=0")
ha.village <- bbw::recode(var = ha.where,
recodes = "5=1;NA=NA;else=0")
ha.eho <- bbw::recode(var = ha.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ha.dry <- as.integer(df$ancnow_ha_dist_dry)
ha.dry.lt15 <- bbw::recode(var = ha.dry,
recodes = "1=1;NA=NA;else=0")
ha.dry.gteq15lt60 <- bbw::recode(var = ha.dry,
recodes = "2=1;NA=NA;else=0")
ha.dry.gteq60lt120 <- bbw::recode(var = ha.dry,
recodes = "3=1;NA=NA;else=0")
ha.dry.gteq120lt360 <- bbw::recode(var = ha.dry,
recodes = "4=1;NA=NA;else=0")
ha.dry.gteq360lt720 <- bbw::recode(var = ha.dry,
recodes = "5=1;NA=NA;else=0")
ha.dry.gteq720lt1440 <- bbw::recode(var = ha.dry,
recodes = "6=1;NA=NA;else=0")
ha.dry.gteq1440 <- bbw::recode(var = ha.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ha.wet <- as.integer(df$ancnow_ha_dist_wet)
ha.wet.lt15 <- bbw::recode(var = ha.wet,
recodes = "1=1;NA=NA;else=0")
ha.wet.gteq15lt60 <- bbw::recode(var = ha.wet,
recodes = "2=1;NA=NA;else=0")
ha.wet.gteq60lt120 <- bbw::recode(var = ha.wet,
recodes = "3=1;NA=NA;else=0")
ha.wet.gteq120lt360 <- bbw::recode(var = ha.wet,
recodes = "4=1;NA=NA;else=0")
ha.wet.gteq360lt720 <- bbw::recode(var = ha.wet,
recodes = "5=1;NA=NA;else=0")
ha.wet.gteq720lt1440 <- bbw::recode(var = ha.wet,
recodes = "6=1;NA=NA;else=0")
ha.wet.gteq1440 <- bbw::recode(var = ha.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ha.visit <- as.integer(df$ancnow_ha_visit)
## Number of visits per trimester
ha.visit.first <- as.integer(df$ancnow_ha_1tri_times)
ha.visit.second <- as.integer(df$ancnow_ha_2tri_times)
ha.visit.third <- as.integer(df$ancnow_ha_3tri_times)
## Concatenate ha provider data.frame
ha <- data.frame(ha, ha.where, ha.home,
ha.gov, ha.private, ha.srhc,
ha.village, ha.eho, ha.dry,
ha.dry.lt15, ha.dry.gteq15lt60,
ha.dry.gteq60lt120, ha.dry.gteq120lt360,
ha.dry.gteq360lt720, ha.dry.gteq720lt1440,
ha.dry.gteq1440, ha.wet,
ha.wet.lt15, ha.wet.gteq15lt60,
ha.wet.gteq60lt120, ha.wet.gteq120lt360,
ha.wet.gteq360lt720, ha.wet.gteq720lt1440,
ha.wet.gteq1440, ha.visit,
ha.visit.first, ha.visit.second,
ha.visit.third)
} else {
## Attend ha
ha <- as.integer(df$ancpast_who.4)
## Where ha
ha.where <- as.integer(df$ancpast_ha_where)
ha.home <- bbw::recode(var = ha.where,
recodes = "1=1;NA=NA;else=0")
ha.gov <- bbw::recode(var = ha.where,
recodes = "2=1;NA=NA;else=0")
ha.private <- bbw::recode(var = ha.where,
recodes = "3=1;NA=NA;else=0")
ha.srhc <- bbw::recode(var = ha.where,
recodes = "4=1;NA=NA;else=0")
ha.village <- bbw::recode(var = ha.where,
recodes = "5=1;NA=NA;else=0")
ha.eho <- bbw::recode(var = ha.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ha.dry <- as.integer(df$ancpast_ha_dist_dry)
ha.dry.lt15 <- bbw::recode(var = ha.dry,
recodes = "1=1;NA=NA;else=0")
ha.dry.gteq15lt60 <- bbw::recode(var = ha.dry,
recodes = "2=1;NA=NA;else=0")
ha.dry.gteq60lt120 <- bbw::recode(var = ha.dry,
recodes = "3=1;NA=NA;else=0")
ha.dry.gteq120lt360 <- bbw::recode(var = ha.dry,
recodes = "4=1;NA=NA;else=0")
ha.dry.gteq360lt720 <- bbw::recode(var = ha.dry,
recodes = "5=1;NA=NA;else=0")
ha.dry.gteq720lt1440 <- bbw::recode(var = ha.dry,
recodes = "6=1;NA=NA;else=0")
ha.dry.gteq1440 <- bbw::recode(var = ha.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ha.wet <- as.integer(df$ancpast_ha_dist_wet)
ha.wet.lt15 <- bbw::recode(var = ha.wet,
recodes = "1=1;NA=NA;else=0")
ha.wet.gteq15lt60 <- bbw::recode(var = ha.wet,
recodes = "2=1;NA=NA;else=0")
ha.wet.gteq60lt120 <- bbw::recode(var = ha.wet,
recodes = "3=1;NA=NA;else=0")
ha.wet.gteq120lt360 <- bbw::recode(var = ha.wet,
recodes = "4=1;NA=NA;else=0")
ha.wet.gteq360lt720 <- bbw::recode(var = ha.wet,
recodes = "5=1;NA=NA;else=0")
ha.wet.gteq720lt1440 <- bbw::recode(var = ha.wet,
recodes = "6=1;NA=NA;else=0")
ha.wet.gteq1440 <- bbw::recode(var = ha.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ha.visit <- as.integer(df$ancpast_ha_visit)
## Number of visits per trimester
ha.visit.first <- as.integer(df$ancpast_ha_1tri_times)
ha.visit.second <- as.integer(df$ancpast_ha_2tri_times)
ha.visit.third <- as.integer(df$ancpast_ha_3tri_times)
## Concatenate ha provider data.frame
ha <- data.frame(ha, ha.where, ha.home,
ha.gov, ha.private, ha.srhc,
ha.village, ha.eho, ha.dry,
ha.dry.lt15, ha.dry.gteq15lt60,
ha.dry.gteq60lt120, ha.dry.gteq120lt360,
ha.dry.gteq360lt720, ha.dry.gteq720lt1440,
ha.dry.gteq1440, ha.wet,
ha.wet.lt15, ha.wet.gteq15lt60,
ha.wet.gteq60lt120, ha.wet.gteq120lt360,
ha.wet.gteq360lt720, ha.wet.gteq720lt1440,
ha.wet.gteq1440, ha.visit,
ha.visit.first, ha.visit.second,
ha.visit.third)
}
## Return data.frame
return(ha)
}
################################################################################
#
#' Function to recode the private doctor ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded private doctor ANC provider information
#'
#' @examples
#' ## Recode private doctor provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_pdoc(df = x, status = "current")
#'
#' ## Recode private doctor provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_pdoc(df = x, status = "past")
#' @export
#'
#'
#
################################################################################
recode_provider_pdoc <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend pdoc
pdoc <- as.integer(df$ancnow_who.5)
## Where pdoc
pdoc.where <- as.integer(df$ancnow_pdoc_where)
pdoc.home <- bbw::recode(var = pdoc.where,
recodes = "1=1;NA=NA;else=0")
pdoc.gov <- bbw::recode(var = pdoc.where,
recodes = "2=1;NA=NA;else=0")
pdoc.private <- bbw::recode(var = pdoc.where,
recodes = "3=1;NA=NA;else=0")
pdoc.srhc <- bbw::recode(var = pdoc.where,
recodes = "4=1;NA=NA;else=0")
pdoc.village <- bbw::recode(var = pdoc.where,
recodes = "5=1;NA=NA;else=0")
pdoc.eho <- bbw::recode(var = pdoc.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
pdoc.dry <- as.integer(df$ancnow_pdoc_dist_dry)
pdoc.dry.lt15 <- bbw::recode(var = pdoc.dry,
recodes = "1=1;NA=NA;else=0")
pdoc.dry.gteq15lt60 <- bbw::recode(var = pdoc.dry,
recodes = "2=1;NA=NA;else=0")
pdoc.dry.gteq60lt120 <- bbw::recode(var = pdoc.dry,
recodes = "3=1;NA=NA;else=0")
pdoc.dry.gteq120lt360 <- bbw::recode(var = pdoc.dry,
recodes = "4=1;NA=NA;else=0")
pdoc.dry.gteq360lt720 <- bbw::recode(var = pdoc.dry,
recodes = "5=1;NA=NA;else=0")
pdoc.dry.gteq720lt1440 <- bbw::recode(var = pdoc.dry,
recodes = "6=1;NA=NA;else=0")
pdoc.dry.gteq1440 <- bbw::recode(var = pdoc.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
pdoc.wet <- as.integer(df$ancnow_pdoc_dist_wet)
pdoc.wet.lt15 <- bbw::recode(var = pdoc.wet,
recodes = "1=1;NA=NA;else=0")
pdoc.wet.gteq15lt60 <- bbw::recode(var = pdoc.wet,
recodes = "2=1;NA=NA;else=0")
pdoc.wet.gteq60lt120 <- bbw::recode(var = pdoc.wet,
recodes = "3=1;NA=NA;else=0")
pdoc.wet.gteq120lt360 <- bbw::recode(var = pdoc.wet,
recodes = "4=1;NA=NA;else=0")
pdoc.wet.gteq360lt720 <- bbw::recode(var = pdoc.wet,
recodes = "5=1;NA=NA;else=0")
pdoc.wet.gteq720lt1440 <- bbw::recode(var = pdoc.wet,
recodes = "6=1;NA=NA;else=0")
pdoc.wet.gteq1440 <- bbw::recode(var = pdoc.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
pdoc.visit <- as.integer(df$ancnow_pdoc_visit)
## Number of visits per trimester
pdoc.visit.first <- as.integer(df$ancnow_pdoc_1tri_times)
pdoc.visit.second <- as.integer(df$ancnow_pdoc_2tri_times)
pdoc.visit.third <- as.integer(df$ancnow_pdoc_3tri_times)
## Concatenate pdoc provider data.frame
pdoc <- data.frame(pdoc, pdoc.where, pdoc.home,
pdoc.gov, pdoc.private, pdoc.srhc,
pdoc.village, pdoc.eho, pdoc.dry,
pdoc.dry.lt15, pdoc.dry.gteq15lt60,
pdoc.dry.gteq60lt120, pdoc.dry.gteq120lt360,
pdoc.dry.gteq360lt720, pdoc.dry.gteq720lt1440,
pdoc.dry.gteq1440, pdoc.wet,
pdoc.wet.lt15, pdoc.wet.gteq15lt60,
pdoc.wet.gteq60lt120, pdoc.wet.gteq120lt360,
pdoc.wet.gteq360lt720, pdoc.wet.gteq720lt1440,
pdoc.wet.gteq1440, pdoc.visit,
pdoc.visit.first, pdoc.visit.second,
pdoc.visit.third)
} else {
## Attend pdoc
pdoc <- as.integer(df$ancpast_who.5)
## Where pdoc
pdoc.where <- as.integer(df$ancpast_pdoc_where)
pdoc.home <- bbw::recode(var = pdoc.where,
recodes = "1=1;NA=NA;else=0")
pdoc.gov <- bbw::recode(var = pdoc.where,
recodes = "2=1;NA=NA;else=0")
pdoc.private <- bbw::recode(var = pdoc.where,
recodes = "3=1;NA=NA;else=0")
pdoc.srhc <- bbw::recode(var = pdoc.where,
recodes = "4=1;NA=NA;else=0")
pdoc.village <- bbw::recode(var = pdoc.where,
recodes = "5=1;NA=NA;else=0")
pdoc.eho <- bbw::recode(var = pdoc.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
pdoc.dry <- as.integer(df$ancpast_pdoc_dist_dry)
pdoc.dry.lt15 <- bbw::recode(var = pdoc.dry,
recodes = "1=1;NA=NA;else=0")
pdoc.dry.gteq15lt60 <- bbw::recode(var = pdoc.dry,
recodes = "2=1;NA=NA;else=0")
pdoc.dry.gteq60lt120 <- bbw::recode(var = pdoc.dry,
recodes = "3=1;NA=NA;else=0")
pdoc.dry.gteq120lt360 <- bbw::recode(var = pdoc.dry,
recodes = "4=1;NA=NA;else=0")
pdoc.dry.gteq360lt720 <- bbw::recode(var = pdoc.dry,
recodes = "5=1;NA=NA;else=0")
pdoc.dry.gteq720lt1440 <- bbw::recode(var = pdoc.dry,
recodes = "6=1;NA=NA;else=0")
pdoc.dry.gteq1440 <- bbw::recode(var = pdoc.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
pdoc.wet <- as.integer(df$ancpast_pdoc_dist_wet)
pdoc.wet.lt15 <- bbw::recode(var = pdoc.wet,
recodes = "1=1;NA=NA;else=0")
pdoc.wet.gteq15lt60 <- bbw::recode(var = pdoc.wet,
recodes = "2=1;NA=NA;else=0")
pdoc.wet.gteq60lt120 <- bbw::recode(var = pdoc.wet,
recodes = "3=1;NA=NA;else=0")
pdoc.wet.gteq120lt360 <- bbw::recode(var = pdoc.wet,
recodes = "4=1;NA=NA;else=0")
pdoc.wet.gteq360lt720 <- bbw::recode(var = pdoc.wet,
recodes = "5=1;NA=NA;else=0")
pdoc.wet.gteq720lt1440 <- bbw::recode(var = pdoc.wet,
recodes = "6=1;NA=NA;else=0")
pdoc.wet.gteq1440 <- bbw::recode(var = pdoc.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
pdoc.visit <- as.integer(df$ancpast_pdoc_visit)
## Number of visits per trimester
pdoc.visit.first <- as.integer(df$ancpast_pdoc_1tri_times)
pdoc.visit.second <- as.integer(df$ancpast_pdoc_2tri_times)
pdoc.visit.third <- as.integer(df$ancpast_pdoc_3tri_times)
## Concatenate pdoc provider data.frame
pdoc <- data.frame(pdoc, pdoc.where, pdoc.home,
pdoc.gov, pdoc.private, pdoc.srhc,
pdoc.village, pdoc.eho, pdoc.dry,
pdoc.dry.lt15, pdoc.dry.gteq15lt60,
pdoc.dry.gteq60lt120, pdoc.dry.gteq120lt360,
pdoc.dry.gteq360lt720, pdoc.dry.gteq720lt1440,
pdoc.dry.gteq1440, pdoc.wet,
pdoc.wet.lt15, pdoc.wet.gteq15lt60,
pdoc.wet.gteq60lt120, pdoc.wet.gteq120lt360,
pdoc.wet.gteq360lt720, pdoc.wet.gteq720lt1440,
pdoc.wet.gteq1440, pdoc.visit,
pdoc.visit.first, pdoc.visit.second,
pdoc.visit.third)
}
## Return data.frame
return(pdoc)
}
################################################################################
#
#' Function to recode the lady health visitor ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded lady health visitor ANC provider information
#'
#' @examples
#' ## Recode lady health visitor provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_lhv(df = x, status = "current")
#'
#' ## Recode lady health visitor provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_lhv(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_lhv <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend lhv
lhv <- as.integer(df$ancnow_who.6)
## Where lhv
lhv.where <- as.integer(df$ancnow_lhv_where)
lhv.home <- bbw::recode(var = lhv.where,
recodes = "1=1;NA=NA;else=0")
lhv.gov <- bbw::recode(var = lhv.where,
recodes = "2=1;NA=NA;else=0")
lhv.private <- bbw::recode(var = lhv.where,
recodes = "3=1;NA=NA;else=0")
lhv.srhc <- bbw::recode(var = lhv.where,
recodes = "4=1;NA=NA;else=0")
lhv.village <- bbw::recode(var = lhv.where,
recodes = "5=1;NA=NA;else=0")
lhv.eho <- bbw::recode(var = lhv.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
lhv.dry <- as.integer(df$ancnow_lhv_dist_dry)
lhv.dry.lt15 <- bbw::recode(var = lhv.dry,
recodes = "1=1;NA=NA;else=0")
lhv.dry.gteq15lt60 <- bbw::recode(var = lhv.dry,
recodes = "2=1;NA=NA;else=0")
lhv.dry.gteq60lt120 <- bbw::recode(var = lhv.dry,
recodes = "3=1;NA=NA;else=0")
lhv.dry.gteq120lt360 <- bbw::recode(var = lhv.dry,
recodes = "4=1;NA=NA;else=0")
lhv.dry.gteq360lt720 <- bbw::recode(var = lhv.dry,
recodes = "5=1;NA=NA;else=0")
lhv.dry.gteq720lt1440 <- bbw::recode(var = lhv.dry,
recodes = "6=1;NA=NA;else=0")
lhv.dry.gteq1440 <- bbw::recode(var = lhv.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
lhv.wet <- as.integer(df$ancnow_lhv_dist_wet)
lhv.wet.lt15 <- bbw::recode(var = lhv.wet,
recodes = "1=1;NA=NA;else=0")
lhv.wet.gteq15lt60 <- bbw::recode(var = lhv.wet,
recodes = "2=1;NA=NA;else=0")
lhv.wet.gteq60lt120 <- bbw::recode(var = lhv.wet,
recodes = "3=1;NA=NA;else=0")
lhv.wet.gteq120lt360 <- bbw::recode(var = lhv.wet,
recodes = "4=1;NA=NA;else=0")
lhv.wet.gteq360lt720 <- bbw::recode(var = lhv.wet,
recodes = "5=1;NA=NA;else=0")
lhv.wet.gteq720lt1440 <- bbw::recode(var = lhv.wet,
recodes = "6=1;NA=NA;else=0")
lhv.wet.gteq1440 <- bbw::recode(var = lhv.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
lhv.visit <- as.integer(df$ancnow_lhv_visit)
## Number of visits per trimester
lhv.visit.first <- as.integer(df$ancnow_lhv_1tri_times)
lhv.visit.second <- as.integer(df$ancnow_lhv_2tri_times)
lhv.visit.third <- as.integer(df$ancnow_lhv_3tri_times)
## Concatenate lhv provider data.frame
lhv <- data.frame(lhv, lhv.where, lhv.home,
lhv.gov, lhv.private, lhv.srhc,
lhv.village, lhv.eho, lhv.dry,
lhv.dry.lt15, lhv.dry.gteq15lt60,
lhv.dry.gteq60lt120, lhv.dry.gteq120lt360,
lhv.dry.gteq360lt720, lhv.dry.gteq720lt1440,
lhv.dry.gteq1440, lhv.wet,
lhv.wet.lt15, lhv.wet.gteq15lt60,
lhv.wet.gteq60lt120, lhv.wet.gteq120lt360,
lhv.wet.gteq360lt720, lhv.wet.gteq720lt1440,
lhv.wet.gteq1440, lhv.visit,
lhv.visit.first, lhv.visit.second,
lhv.visit.third)
} else {
## Attend lhv
lhv <- as.integer(df$ancpast_who.6)
## Where lhv
lhv.where <- as.integer(df$ancpast_lhv_where)
lhv.home <- bbw::recode(var = lhv.where,
recodes = "1=1;NA=NA;else=0")
lhv.gov <- bbw::recode(var = lhv.where,
recodes = "2=1;NA=NA;else=0")
lhv.private <- bbw::recode(var = lhv.where,
recodes = "3=1;NA=NA;else=0")
lhv.srhc <- bbw::recode(var = lhv.where,
recodes = "4=1;NA=NA;else=0")
lhv.village <- bbw::recode(var = lhv.where,
recodes = "5=1;NA=NA;else=0")
lhv.eho <- bbw::recode(var = lhv.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
lhv.dry <- as.integer(df$ancpast_lhv_dist_dry)
lhv.dry.lt15 <- bbw::recode(var = lhv.dry,
recodes = "1=1;NA=NA;else=0")
lhv.dry.gteq15lt60 <- bbw::recode(var = lhv.dry,
recodes = "2=1;NA=NA;else=0")
lhv.dry.gteq60lt120 <- bbw::recode(var = lhv.dry,
recodes = "3=1;NA=NA;else=0")
lhv.dry.gteq120lt360 <- bbw::recode(var = lhv.dry,
recodes = "4=1;NA=NA;else=0")
lhv.dry.gteq360lt720 <- bbw::recode(var = lhv.dry,
recodes = "5=1;NA=NA;else=0")
lhv.dry.gteq720lt1440 <- bbw::recode(var = lhv.dry,
recodes = "6=1;NA=NA;else=0")
lhv.dry.gteq1440 <- bbw::recode(var = lhv.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
lhv.wet <- as.integer(df$ancpast_lhv_dist_wet)
lhv.wet.lt15 <- bbw::recode(var = lhv.wet,
recodes = "1=1;NA=NA;else=0")
lhv.wet.gteq15lt60 <- bbw::recode(var = lhv.wet,
recodes = "2=1;NA=NA;else=0")
lhv.wet.gteq60lt120 <- bbw::recode(var = lhv.wet,
recodes = "3=1;NA=NA;else=0")
lhv.wet.gteq120lt360 <- bbw::recode(var = lhv.wet,
recodes = "4=1;NA=NA;else=0")
lhv.wet.gteq360lt720 <- bbw::recode(var = lhv.wet,
recodes = "5=1;NA=NA;else=0")
lhv.wet.gteq720lt1440 <- bbw::recode(var = lhv.wet,
recodes = "6=1;NA=NA;else=0")
lhv.wet.gteq1440 <- bbw::recode(var = lhv.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
lhv.visit <- as.integer(df$ancpast_lhv_visit)
## Number of visits per trimester
lhv.visit.first <- as.integer(df$ancpast_lhv_1tri_times)
lhv.visit.second <- as.integer(df$ancpast_lhv_2tri_times)
lhv.visit.third <- as.integer(df$ancpast_lhv_3tri_times)
## Concatenate lhv provider data.frame
lhv <- data.frame(lhv, lhv.where, lhv.home,
lhv.gov, lhv.private, lhv.srhc,
lhv.village, lhv.eho, lhv.dry,
lhv.dry.lt15, lhv.dry.gteq15lt60,
lhv.dry.gteq60lt120, lhv.dry.gteq120lt360,
lhv.dry.gteq360lt720, lhv.dry.gteq720lt1440,
lhv.dry.gteq1440, lhv.wet,
lhv.wet.lt15, lhv.wet.gteq15lt60,
lhv.wet.gteq60lt120, lhv.wet.gteq120lt360,
lhv.wet.gteq360lt720, lhv.wet.gteq720lt1440,
lhv.wet.gteq1440, lhv.visit,
lhv.visit.first, lhv.visit.second,
lhv.visit.third)
}
## Return data.frame
return(lhv)
}
################################################################################
#
#' Function to recode the midwife ANC provider data for the Myanmar MCCT
#' Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded midwife ANC provider information
#'
#' @examples
#' ## Recode midwife provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_midwife(df = x, status = "current")
#'
#' ## Recode midwife provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_midwife(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_midwife <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend midwife
midwife <- as.integer(df$ancnow_who.7)
## Where midwife
midwife.where <- as.integer(df$ancnow_mw_where)
midwife.home <- bbw::recode(var = midwife.where,
recodes = "1=1;NA=NA;else=0")
midwife.gov <- bbw::recode(var = midwife.where,
recodes = "2=1;NA=NA;else=0")
midwife.private <- bbw::recode(var = midwife.where,
recodes = "3=1;NA=NA;else=0")
midwife.srhc <- bbw::recode(var = midwife.where,
recodes = "4=1;NA=NA;else=0")
midwife.village <- bbw::recode(var = midwife.where,
recodes = "5=1;NA=NA;else=0")
midwife.eho <- bbw::recode(var = midwife.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
midwife.dry <- as.integer(df$ancnow_mw_dist_dry)
midwife.dry.lt15 <- bbw::recode(var = midwife.dry,
recodes = "1=1;NA=NA;else=0")
midwife.dry.gteq15lt60 <- bbw::recode(var = midwife.dry,
recodes = "2=1;NA=NA;else=0")
midwife.dry.gteq60lt120 <- bbw::recode(var = midwife.dry,
recodes = "3=1;NA=NA;else=0")
midwife.dry.gteq120lt360 <- bbw::recode(var = midwife.dry,
recodes = "4=1;NA=NA;else=0")
midwife.dry.gteq360lt720 <- bbw::recode(var = midwife.dry,
recodes = "5=1;NA=NA;else=0")
midwife.dry.gteq720lt1440 <- bbw::recode(var = midwife.dry,
recodes = "6=1;NA=NA;else=0")
midwife.dry.gteq1440 <- bbw::recode(var = midwife.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
midwife.wet <- as.integer(df$ancnow_mw_dist_wet)
midwife.wet.lt15 <- bbw::recode(var = midwife.wet,
recodes = "1=1;NA=NA;else=0")
midwife.wet.gteq15lt60 <- bbw::recode(var = midwife.wet,
recodes = "2=1;NA=NA;else=0")
midwife.wet.gteq60lt120 <- bbw::recode(var = midwife.wet,
recodes = "3=1;NA=NA;else=0")
midwife.wet.gteq120lt360 <- bbw::recode(var = midwife.wet,
recodes = "4=1;NA=NA;else=0")
midwife.wet.gteq360lt720 <- bbw::recode(var = midwife.wet,
recodes = "5=1;NA=NA;else=0")
midwife.wet.gteq720lt1440 <- bbw::recode(var = midwife.wet,
recodes = "6=1;NA=NA;else=0")
midwife.wet.gteq1440 <- bbw::recode(var = midwife.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
midwife.visit <- as.integer(df$ancnow_mw_visit)
## Number of visits per trimester
midwife.visit.first <- as.integer(df$ancnow_mw_1tri_times)
midwife.visit.second <- as.integer(df$ancnow_mw_2tri_times)
midwife.visit.third <- as.integer(df$ancnow_mw_3tri_times)
## Concatenate midwife provider data.frame
midwife <- data.frame(midwife, midwife.where, midwife.home,
midwife.gov, midwife.private, midwife.srhc,
midwife.village, midwife.eho, midwife.dry,
midwife.dry.lt15, midwife.dry.gteq15lt60,
midwife.dry.gteq60lt120, midwife.dry.gteq120lt360,
midwife.dry.gteq360lt720, midwife.dry.gteq720lt1440,
midwife.dry.gteq1440, midwife.wet,
midwife.wet.lt15, midwife.wet.gteq15lt60,
midwife.wet.gteq60lt120, midwife.wet.gteq120lt360,
midwife.wet.gteq360lt720, midwife.wet.gteq720lt1440,
midwife.wet.gteq1440, midwife.visit,
midwife.visit.first, midwife.visit.second,
midwife.visit.third)
} else {
## Attend midwife
midwife <- as.integer(df$ancpast_who.7)
## Where midwife
midwife.where <- as.integer(df$ancpast_mw_where)
midwife.home <- bbw::recode(var = midwife.where,
recodes = "1=1;NA=NA;else=0")
midwife.gov <- bbw::recode(var = midwife.where,
recodes = "2=1;NA=NA;else=0")
midwife.private <- bbw::recode(var = midwife.where,
recodes = "3=1;NA=NA;else=0")
midwife.srhc <- bbw::recode(var = midwife.where,
recodes = "4=1;NA=NA;else=0")
midwife.village <- bbw::recode(var = midwife.where,
recodes = "5=1;NA=NA;else=0")
midwife.eho <- bbw::recode(var = midwife.where,
recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
midwife.dry <- as.integer(df$ancpast_mw_dist_dry)
midwife.dry.lt15 <- bbw::recode(var = midwife.dry,
recodes = "1=1;NA=NA;else=0")
midwife.dry.gteq15lt60 <- bbw::recode(var = midwife.dry,
recodes = "2=1;NA=NA;else=0")
midwife.dry.gteq60lt120 <- bbw::recode(var = midwife.dry,
recodes = "3=1;NA=NA;else=0")
midwife.dry.gteq120lt360 <- bbw::recode(var = midwife.dry,
recodes = "4=1;NA=NA;else=0")
midwife.dry.gteq360lt720 <- bbw::recode(var = midwife.dry,
recodes = "5=1;NA=NA;else=0")
midwife.dry.gteq720lt1440 <- bbw::recode(var = midwife.dry,
recodes = "6=1;NA=NA;else=0")
midwife.dry.gteq1440 <- bbw::recode(var = midwife.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
midwife.wet <- as.integer(df$ancpast_mw_dist_wet)
midwife.wet.lt15 <- bbw::recode(var = midwife.wet,
recodes = "1=1;NA=NA;else=0")
midwife.wet.gteq15lt60 <- bbw::recode(var = midwife.wet,
recodes = "2=1;NA=NA;else=0")
midwife.wet.gteq60lt120 <- bbw::recode(var = midwife.wet,
recodes = "3=1;NA=NA;else=0")
midwife.wet.gteq120lt360 <- bbw::recode(var = midwife.wet,
recodes = "4=1;NA=NA;else=0")
midwife.wet.gteq360lt720 <- bbw::recode(var = midwife.wet,
recodes = "5=1;NA=NA;else=0")
midwife.wet.gteq720lt1440 <- bbw::recode(var = midwife.wet,
recodes = "6=1;NA=NA;else=0")
midwife.wet.gteq1440 <- bbw::recode(var = midwife.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
midwife.visit <- as.integer(df$ancpast_mw_visit)
## Number of visits per trimester
midwife.visit.first <- as.integer(df$ancpast_mw_1tri_times)
midwife.visit.second <- as.integer(df$ancpast_mw_2tri_times)
midwife.visit.third <- as.integer(df$ancpast_mw_3tri_times)
## Concatenate midwife provider data.frame
midwife <- data.frame(midwife, midwife.where, midwife.home,
midwife.gov, midwife.private, midwife.srhc,
midwife.village, midwife.eho, midwife.dry,
midwife.dry.lt15, midwife.dry.gteq15lt60,
midwife.dry.gteq60lt120, midwife.dry.gteq120lt360,
midwife.dry.gteq360lt720, midwife.dry.gteq720lt1440,
midwife.dry.gteq1440, midwife.wet,
midwife.wet.lt15, midwife.wet.gteq15lt60,
midwife.wet.gteq60lt120, midwife.wet.gteq120lt360,
midwife.wet.gteq360lt720, midwife.wet.gteq720lt1440,
midwife.wet.gteq1440, midwife.visit,
midwife.visit.first, midwife.visit.second,
midwife.visit.third)
}
## Return data.frame
return(midwife)
}
################################################################################
#
#' Function to recode the auxilliary midwife ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded auxilliary midwife ANC provider information
#'
#' @examples
#' ## Recode auxilliary midwife for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_amw(df = x, status = "current")
#'
#' ## Recode auxilliary midwife for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_amw(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_amw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend amw
amw <- as.integer(df$ancnow_who.8)
## Where amw
amw.where <- as.integer(df$ancnow_amw_where)
amw.home <- bbw::recode(var = amw.where, recodes = "1=1;NA=NA;else=0")
amw.gov <- bbw::recode(var = amw.where, recodes = "2=1;NA=NA;else=0")
amw.private <- bbw::recode(var = amw.where, recodes = "3=1;NA=NA;else=0")
amw.srhc <- bbw::recode(var = amw.where, recodes = "4=1;NA=NA;else=0")
amw.village <- bbw::recode(var = amw.where, recodes = "5=1;NA=NA;else=0")
amw.eho <- bbw::recode(var = amw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
amw.dry <- as.integer(df$ancnow_amw_dist_dry)
amw.dry.lt15 <- bbw::recode(var = amw.dry,
recodes = "1=1;NA=NA;else=0")
amw.dry.gteq15lt60 <- bbw::recode(var = amw.dry,
recodes = "2=1;NA=NA;else=0")
amw.dry.gteq60lt120 <- bbw::recode(var = amw.dry,
recodes = "3=1;NA=NA;else=0")
amw.dry.gteq120lt360 <- bbw::recode(var = amw.dry,
recodes = "4=1;NA=NA;else=0")
amw.dry.gteq360lt720 <- bbw::recode(var = amw.dry,
recodes = "5=1;NA=NA;else=0")
amw.dry.gteq720lt1440 <- bbw::recode(var = amw.dry,
recodes = "6=1;NA=NA;else=0")
amw.dry.gteq1440 <- bbw::recode(var = amw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
amw.wet <- as.integer(df$ancnow_amw_dist_wet)
amw.wet.lt15 <- bbw::recode(var = amw.wet,
recodes = "1=1;NA=NA;else=0")
amw.wet.gteq15lt60 <- bbw::recode(var = amw.wet,
recodes = "2=1;NA=NA;else=0")
amw.wet.gteq60lt120 <- bbw::recode(var = amw.wet,
recodes = "3=1;NA=NA;else=0")
amw.wet.gteq120lt360 <- bbw::recode(var = amw.wet,
recodes = "4=1;NA=NA;else=0")
amw.wet.gteq360lt720 <- bbw::recode(var = amw.wet,
recodes = "5=1;NA=NA;else=0")
amw.wet.gteq720lt1440 <- bbw::recode(var = amw.wet,
recodes = "6=1;NA=NA;else=0")
amw.wet.gteq1440 <- bbw::recode(var = amw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
amw.visit <- as.integer(df$ancnow_amw_visit)
## Number of visits per trimester
amw.visit.first <- as.integer(df$ancnow_amw_1tri_times)
amw.visit.second <- as.integer(df$ancnow_amw_2tri_times)
amw.visit.third <- as.integer(df$ancnow_amw_3tri_times)
## Concatenate amw provider data.frame
amw <- data.frame(amw, amw.where, amw.home,
amw.gov, amw.private, amw.srhc,
amw.village, amw.eho, amw.dry,
amw.dry.lt15, amw.dry.gteq15lt60,
amw.dry.gteq60lt120, amw.dry.gteq120lt360,
amw.dry.gteq360lt720, amw.dry.gteq720lt1440,
amw.dry.gteq1440, amw.wet,
amw.wet.lt15, amw.wet.gteq15lt60,
amw.wet.gteq60lt120, amw.wet.gteq120lt360,
amw.wet.gteq360lt720, amw.wet.gteq720lt1440,
amw.wet.gteq1440, amw.visit,
amw.visit.first, amw.visit.second,
amw.visit.third)
} else {
## Attend amw
amw <- as.integer(df$ancpast_who.8)
## Where amw
amw.where <- as.integer(df$ancpast_amw_where)
amw.home <- bbw::recode(var = amw.where, recodes = "1=1;NA=NA;else=0")
amw.gov <- bbw::recode(var = amw.where, recodes = "2=1;NA=NA;else=0")
amw.private <- bbw::recode(var = amw.where, recodes = "3=1;NA=NA;else=0")
amw.srhc <- bbw::recode(var = amw.where, recodes = "4=1;NA=NA;else=0")
amw.village <- bbw::recode(var = amw.where, recodes = "5=1;NA=NA;else=0")
amw.eho <- bbw::recode(var = amw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
amw.dry <- as.integer(df$ancpast_amw_dist_dry)
amw.dry.lt15 <- bbw::recode(var = amw.dry,
recodes = "1=1;NA=NA;else=0")
amw.dry.gteq15lt60 <- bbw::recode(var = amw.dry,
recodes = "2=1;NA=NA;else=0")
amw.dry.gteq60lt120 <- bbw::recode(var = amw.dry,
recodes = "3=1;NA=NA;else=0")
amw.dry.gteq120lt360 <- bbw::recode(var = amw.dry,
recodes = "4=1;NA=NA;else=0")
amw.dry.gteq360lt720 <- bbw::recode(var = amw.dry,
recodes = "5=1;NA=NA;else=0")
amw.dry.gteq720lt1440 <- bbw::recode(var = amw.dry,
recodes = "6=1;NA=NA;else=0")
amw.dry.gteq1440 <- bbw::recode(var = amw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
amw.wet <- as.integer(df$ancpast_amw_dist_wet)
amw.wet.lt15 <- bbw::recode(var = amw.wet,
recodes = "1=1;NA=NA;else=0")
amw.wet.gteq15lt60 <- bbw::recode(var = amw.wet,
recodes = "2=1;NA=NA;else=0")
amw.wet.gteq60lt120 <- bbw::recode(var = amw.wet,
recodes = "3=1;NA=NA;else=0")
amw.wet.gteq120lt360 <- bbw::recode(var = amw.wet,
recodes = "4=1;NA=NA;else=0")
amw.wet.gteq360lt720 <- bbw::recode(var = amw.wet,
recodes = "5=1;NA=NA;else=0")
amw.wet.gteq720lt1440 <- bbw::recode(var = amw.wet,
recodes = "6=1;NA=NA;else=0")
amw.wet.gteq1440 <- bbw::recode(var = amw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
amw.visit <- as.integer(df$ancpast_amw_visit)
## Number of visits per trimester
amw.visit.first <- as.integer(df$ancpast_amw_1tri_times)
amw.visit.second <- as.integer(df$ancpast_amw_2tri_times)
amw.visit.third <- as.integer(df$ancpast_amw_3tri_times)
## Concatenate amw provider data.frame
amw <- data.frame(amw, amw.where, amw.home,
amw.gov, amw.private, amw.srhc,
amw.village, amw.eho, amw.dry,
amw.dry.lt15, amw.dry.gteq15lt60,
amw.dry.gteq60lt120, amw.dry.gteq120lt360,
amw.dry.gteq360lt720, amw.dry.gteq720lt1440,
amw.dry.gteq1440, amw.wet,
amw.wet.lt15, amw.wet.gteq15lt60,
amw.wet.gteq60lt120, amw.wet.gteq120lt360,
amw.wet.gteq360lt720, amw.wet.gteq720lt1440,
amw.wet.gteq1440, amw.visit,
amw.visit.first, amw.visit.second,
amw.visit.third)
}
## Return data.frame
return(amw)
}
################################################################################
#
#' Function to recode the traditional birth attendant ANC provider data for the
#' Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded traditional birth attendant ANC provider
#' information
#'
#' @examples
#' ## Recode tba provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_tba(df = x, status = "current")
#'
#' ## Recode tba provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_tba(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_tba <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend tba
tba <- as.integer(df$ancnow_who.9)
## Where tba
tba.where <- as.integer(df$ancnow_tba_where)
tba.home <- bbw::recode(var = tba.where, recodes = "1=1;NA=NA;else=0")
tba.gov <- bbw::recode(var = tba.where, recodes = "2=1;NA=NA;else=0")
tba.private <- bbw::recode(var = tba.where, recodes = "3=1;NA=NA;else=0")
tba.srhc <- bbw::recode(var = tba.where, recodes = "4=1;NA=NA;else=0")
tba.village <- bbw::recode(var = tba.where, recodes = "5=1;NA=NA;else=0")
tba.eho <- bbw::recode(var = tba.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
tba.dry <- as.integer(df$ancnow_tba_dist_dry)
tba.dry.lt15 <- bbw::recode(var = tba.dry,
recodes = "1=1;NA=NA;else=0")
tba.dry.gteq15lt60 <- bbw::recode(var = tba.dry,
recodes = "2=1;NA=NA;else=0")
tba.dry.gteq60lt120 <- bbw::recode(var = tba.dry,
recodes = "3=1;NA=NA;else=0")
tba.dry.gteq120lt360 <- bbw::recode(var = tba.dry,
recodes = "4=1;NA=NA;else=0")
tba.dry.gteq360lt720 <- bbw::recode(var = tba.dry,
recodes = "5=1;NA=NA;else=0")
tba.dry.gteq720lt1440 <- bbw::recode(var = tba.dry,
recodes = "6=1;NA=NA;else=0")
tba.dry.gteq1440 <- bbw::recode(var = tba.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
tba.wet <- as.integer(df$ancnow_tba_dist_wet)
tba.wet.lt15 <- bbw::recode(var = tba.wet,
recodes = "1=1;NA=NA;else=0")
tba.wet.gteq15lt60 <- bbw::recode(var = tba.wet,
recodes = "2=1;NA=NA;else=0")
tba.wet.gteq60lt120 <- bbw::recode(var = tba.wet,
recodes = "3=1;NA=NA;else=0")
tba.wet.gteq120lt360 <- bbw::recode(var = tba.wet,
recodes = "4=1;NA=NA;else=0")
tba.wet.gteq360lt720 <- bbw::recode(var = tba.wet,
recodes = "5=1;NA=NA;else=0")
tba.wet.gteq720lt1440 <- bbw::recode(var = tba.wet,
recodes = "6=1;NA=NA;else=0")
tba.wet.gteq1440 <- bbw::recode(var = tba.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
tba.visit <- as.integer(df$ancnow_tba_visit)
## Number of visits per trimester
tba.visit.first <- as.integer(df$ancnow_tba_1tri_times)
tba.visit.second <- as.integer(df$ancnow_tba_2tri_times)
tba.visit.third <- as.integer(df$ancnow_tba_3tri_times)
## Concatenate tba provider data.frame
tba <- data.frame(tba, tba.where, tba.home,
tba.gov, tba.private, tba.srhc,
tba.village, tba.eho, tba.dry,
tba.dry.lt15, tba.dry.gteq15lt60,
tba.dry.gteq60lt120, tba.dry.gteq120lt360,
tba.dry.gteq360lt720, tba.dry.gteq720lt1440,
tba.dry.gteq1440, tba.wet,
tba.wet.lt15, tba.wet.gteq15lt60,
tba.wet.gteq60lt120, tba.wet.gteq120lt360,
tba.wet.gteq360lt720, tba.wet.gteq720lt1440,
tba.wet.gteq1440, tba.visit,
tba.visit.first, tba.visit.second,
tba.visit.third)
} else {
## Attend tba
tba <- as.integer(df$ancpast_who.9)
## Where tba
tba.where <- as.integer(df$ancpast_tba_where)
tba.home <- bbw::recode(var = tba.where, recodes = "1=1;NA=NA;else=0")
tba.gov <- bbw::recode(var = tba.where, recodes = "2=1;NA=NA;else=0")
tba.private <- bbw::recode(var = tba.where, recodes = "3=1;NA=NA;else=0")
tba.srhc <- bbw::recode(var = tba.where, recodes = "4=1;NA=NA;else=0")
tba.village <- bbw::recode(var = tba.where, recodes = "5=1;NA=NA;else=0")
tba.eho <- bbw::recode(var = tba.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
tba.dry <- as.integer(df$ancpast_tba_dist_dry)
tba.dry.lt15 <- bbw::recode(var = tba.dry,
recodes = "1=1;NA=NA;else=0")
tba.dry.gteq15lt60 <- bbw::recode(var = tba.dry,
recodes = "2=1;NA=NA;else=0")
tba.dry.gteq60lt120 <- bbw::recode(var = tba.dry,
recodes = "3=1;NA=NA;else=0")
tba.dry.gteq120lt360 <- bbw::recode(var = tba.dry,
recodes = "4=1;NA=NA;else=0")
tba.dry.gteq360lt720 <- bbw::recode(var = tba.dry,
recodes = "5=1;NA=NA;else=0")
tba.dry.gteq720lt1440 <- bbw::recode(var = tba.dry,
recodes = "6=1;NA=NA;else=0")
tba.dry.gteq1440 <- bbw::recode(var = tba.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
tba.wet <- as.integer(df$ancpast_tba_dist_wet)
tba.wet.lt15 <- bbw::recode(var = tba.wet,
recodes = "1=1;NA=NA;else=0")
tba.wet.gteq15lt60 <- bbw::recode(var = tba.wet,
recodes = "2=1;NA=NA;else=0")
tba.wet.gteq60lt120 <- bbw::recode(var = tba.wet,
recodes = "3=1;NA=NA;else=0")
tba.wet.gteq120lt360 <- bbw::recode(var = tba.wet,
recodes = "4=1;NA=NA;else=0")
tba.wet.gteq360lt720 <- bbw::recode(var = tba.wet,
recodes = "5=1;NA=NA;else=0")
tba.wet.gteq720lt1440 <- bbw::recode(var = tba.wet,
recodes = "6=1;NA=NA;else=0")
tba.wet.gteq1440 <- bbw::recode(var = tba.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
tba.visit <- as.integer(df$ancpast_tba_visit)
## Number of visits per trimester
tba.visit.first <- as.integer(df$ancpast_tba_1tri_times)
tba.visit.second <- as.integer(df$ancpast_tba_2tri_times)
tba.visit.third <- as.integer(df$ancpast_tba_3tri_times)
## Concatenate tba provider data.frame
tba <- data.frame(tba, tba.where, tba.home,
tba.gov, tba.private, tba.srhc,
tba.village, tba.eho, tba.dry,
tba.dry.lt15, tba.dry.gteq15lt60,
tba.dry.gteq60lt120, tba.dry.gteq120lt360,
tba.dry.gteq360lt720, tba.dry.gteq720lt1440,
tba.dry.gteq1440, tba.wet,
tba.wet.lt15, tba.wet.gteq15lt60,
tba.wet.gteq60lt120, tba.wet.gteq120lt360,
tba.wet.gteq360lt720, tba.wet.gteq720lt1440,
tba.wet.gteq1440, tba.visit,
tba.visit.first, tba.visit.second,
tba.visit.third)
}
## Return data.frame
return(tba)
}
################################################################################
#
#' Function to recode the community health worker ANC provider data for the
#' Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded community health worker ANC provider
#' information
#'
#' @examples
#' ## Recode chw provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_chw(df = x, status = "current")
#'
#' ## Recode chw provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_chw(df = x, status = "past")
#' @export
#'
#'
#
################################################################################
recode_provider_chw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend chw
chw <- as.integer(df$ancnow_who.10)
## Where chw
chw.where <- as.integer(df$ancnow_chw_where)
chw.home <- bbw::recode(var = chw.where, recodes = "1=1;NA=NA;else=0")
chw.gov <- bbw::recode(var = chw.where, recodes = "2=1;NA=NA;else=0")
chw.private <- bbw::recode(var = chw.where, recodes = "3=1;NA=NA;else=0")
chw.srhc <- bbw::recode(var = chw.where, recodes = "4=1;NA=NA;else=0")
chw.village <- bbw::recode(var = chw.where, recodes = "5=1;NA=NA;else=0")
chw.eho <- bbw::recode(var = chw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
chw.dry <- as.integer(df$ancnow_chw_dist_dry)
chw.dry.lt15 <- bbw::recode(var = chw.dry,
recodes = "1=1;NA=NA;else=0")
chw.dry.gteq15lt60 <- bbw::recode(var = chw.dry,
recodes = "2=1;NA=NA;else=0")
chw.dry.gteq60lt120 <- bbw::recode(var = chw.dry,
recodes = "3=1;NA=NA;else=0")
chw.dry.gteq120lt360 <- bbw::recode(var = chw.dry,
recodes = "4=1;NA=NA;else=0")
chw.dry.gteq360lt720 <- bbw::recode(var = chw.dry,
recodes = "5=1;NA=NA;else=0")
chw.dry.gteq720lt1440 <- bbw::recode(var = chw.dry,
recodes = "6=1;NA=NA;else=0")
chw.dry.gteq1440 <- bbw::recode(var = chw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
chw.wet <- as.integer(df$ancnow_chw_dist_wet)
chw.wet.lt15 <- bbw::recode(var = chw.wet,
recodes = "1=1;NA=NA;else=0")
chw.wet.gteq15lt60 <- bbw::recode(var = chw.wet,
recodes = "2=1;NA=NA;else=0")
chw.wet.gteq60lt120 <- bbw::recode(var = chw.wet,
recodes = "3=1;NA=NA;else=0")
chw.wet.gteq120lt360 <- bbw::recode(var = chw.wet,
recodes = "4=1;NA=NA;else=0")
chw.wet.gteq360lt720 <- bbw::recode(var = chw.wet,
recodes = "5=1;NA=NA;else=0")
chw.wet.gteq720lt1440 <- bbw::recode(var = chw.wet,
recodes = "6=1;NA=NA;else=0")
chw.wet.gteq1440 <- bbw::recode(var = chw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
chw.visit <- as.integer(df$ancnow_chw_visit)
## Number of visits per trimester
chw.visit.first <- as.integer(df$ancnow_chw_1tri_times)
chw.visit.second <- as.integer(df$ancnow_chw_2tri_times)
chw.visit.third <- as.integer(df$ancnow_chw_3tri_times)
## Concatenate chw provider data.frame
chw <- data.frame(chw, chw.where, chw.home,
chw.gov, chw.private, chw.srhc,
chw.village, chw.eho, chw.dry,
chw.dry.lt15, chw.dry.gteq15lt60,
chw.dry.gteq60lt120, chw.dry.gteq120lt360,
chw.dry.gteq360lt720, chw.dry.gteq720lt1440,
chw.dry.gteq1440, chw.wet,
chw.wet.lt15, chw.wet.gteq15lt60,
chw.wet.gteq60lt120, chw.wet.gteq120lt360,
chw.wet.gteq360lt720, chw.wet.gteq720lt1440,
chw.wet.gteq1440, chw.visit,
chw.visit.first, chw.visit.second,
chw.visit.third)
} else {
## Attend chw
chw <- as.integer(df$ancpast_who.10)
## Where chw
chw.where <- as.integer(df$ancpast_chw_where)
chw.home <- bbw::recode(var = chw.where, recodes = "1=1;NA=NA;else=0")
chw.gov <- bbw::recode(var = chw.where, recodes = "2=1;NA=NA;else=0")
chw.private <- bbw::recode(var = chw.where, recodes = "3=1;NA=NA;else=0")
chw.srhc <- bbw::recode(var = chw.where, recodes = "4=1;NA=NA;else=0")
chw.village <- bbw::recode(var = chw.where, recodes = "5=1;NA=NA;else=0")
chw.eho <- bbw::recode(var = chw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
chw.dry <- as.integer(df$ancpast_chw_dist_dry)
chw.dry.lt15 <- bbw::recode(var = chw.dry,
recodes = "1=1;NA=NA;else=0")
chw.dry.gteq15lt60 <- bbw::recode(var = chw.dry,
recodes = "2=1;NA=NA;else=0")
chw.dry.gteq60lt120 <- bbw::recode(var = chw.dry,
recodes = "3=1;NA=NA;else=0")
chw.dry.gteq120lt360 <- bbw::recode(var = chw.dry,
recodes = "4=1;NA=NA;else=0")
chw.dry.gteq360lt720 <- bbw::recode(var = chw.dry,
recodes = "5=1;NA=NA;else=0")
chw.dry.gteq720lt1440 <- bbw::recode(var = chw.dry,
recodes = "6=1;NA=NA;else=0")
chw.dry.gteq1440 <- bbw::recode(var = chw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
chw.wet <- as.integer(df$ancpast_chw_dist_wet)
chw.wet.lt15 <- bbw::recode(var = chw.wet,
recodes = "1=1;NA=NA;else=0")
chw.wet.gteq15lt60 <- bbw::recode(var = chw.wet,
recodes = "2=1;NA=NA;else=0")
chw.wet.gteq60lt120 <- bbw::recode(var = chw.wet,
recodes = "3=1;NA=NA;else=0")
chw.wet.gteq120lt360 <- bbw::recode(var = chw.wet,
recodes = "4=1;NA=NA;else=0")
chw.wet.gteq360lt720 <- bbw::recode(var = chw.wet,
recodes = "5=1;NA=NA;else=0")
chw.wet.gteq720lt1440 <- bbw::recode(var = chw.wet,
recodes = "6=1;NA=NA;else=0")
chw.wet.gteq1440 <- bbw::recode(var = chw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
chw.visit <- as.integer(df$ancpast_chw_visit)
## Number of visits per trimester
chw.visit.first <- as.integer(df$ancpast_chw_1tri_times)
chw.visit.second <- as.integer(df$ancpast_chw_2tri_times)
chw.visit.third <- as.integer(df$ancpast_chw_3tri_times)
## Concatenate chw provider data.frame
chw <- data.frame(chw, chw.where, chw.home,
chw.gov, chw.private, chw.srhc,
chw.village, chw.eho, chw.dry,
chw.dry.lt15, chw.dry.gteq15lt60,
chw.dry.gteq60lt120, chw.dry.gteq120lt360,
chw.dry.gteq360lt720, chw.dry.gteq720lt1440,
chw.dry.gteq1440, chw.wet,
chw.wet.lt15, chw.wet.gteq15lt60,
chw.wet.gteq60lt120, chw.wet.gteq120lt360,
chw.wet.gteq360lt720, chw.wet.gteq720lt1440,
chw.wet.gteq1440, chw.visit,
chw.visit.first, chw.visit.second,
chw.visit.third)
}
## Return data.frame
return(chw)
}
################################################################################
#
#' Function to recode the ethnic health worker ANC provider data for the Myanmar
#' MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded ethnic health worker ANC provider information
#'
#' @examples
#' ## Recode ehw provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_provider_ehw(df = x, status = "current")
#'
#' ## Recode ehw provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_provider_ehw(df = x, status = "past")
#'
#' @export
#'
#'
#
################################################################################
recode_provider_ehw <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Attend ehw
ehw <- as.integer(df$ancnow_who.11)
## Where ehw
ehw.where <- as.integer(df$ancnow_ehw_where)
ehw.home <- bbw::recode(var = ehw.where, recodes = "1=1;NA=NA;else=0")
ehw.gov <- bbw::recode(var = ehw.where, recodes = "2=1;NA=NA;else=0")
ehw.private <- bbw::recode(var = ehw.where, recodes = "3=1;NA=NA;else=0")
ehw.srhc <- bbw::recode(var = ehw.where, recodes = "4=1;NA=NA;else=0")
ehw.village <- bbw::recode(var = ehw.where, recodes = "5=1;NA=NA;else=0")
ehw.eho <- bbw::recode(var = ehw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ehw.dry <- as.integer(df$ancnow_ehw_dist_dry)
ehw.dry.lt15 <- bbw::recode(var = ehw.dry,
recodes = "1=1;NA=NA;else=0")
ehw.dry.gteq15lt60 <- bbw::recode(var = ehw.dry,
recodes = "2=1;NA=NA;else=0")
ehw.dry.gteq60lt120 <- bbw::recode(var = ehw.dry,
recodes = "3=1;NA=NA;else=0")
ehw.dry.gteq120lt360 <- bbw::recode(var = ehw.dry,
recodes = "4=1;NA=NA;else=0")
ehw.dry.gteq360lt720 <- bbw::recode(var = ehw.dry,
recodes = "5=1;NA=NA;else=0")
ehw.dry.gteq720lt1440 <- bbw::recode(var = ehw.dry,
recodes = "6=1;NA=NA;else=0")
ehw.dry.gteq1440 <- bbw::recode(var = ehw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ehw.wet <- as.integer(df$ancnow_ehw_dist_wet)
ehw.wet.lt15 <- bbw::recode(var = ehw.wet,
recodes = "1=1;NA=NA;else=0")
ehw.wet.gteq15lt60 <- bbw::recode(var = ehw.wet,
recodes = "2=1;NA=NA;else=0")
ehw.wet.gteq60lt120 <- bbw::recode(var = ehw.wet,
recodes = "3=1;NA=NA;else=0")
ehw.wet.gteq120lt360 <- bbw::recode(var = ehw.wet,
recodes = "4=1;NA=NA;else=0")
ehw.wet.gteq360lt720 <- bbw::recode(var = ehw.wet,
recodes = "5=1;NA=NA;else=0")
ehw.wet.gteq720lt1440 <- bbw::recode(var = ehw.wet,
recodes = "6=1;NA=NA;else=0")
ehw.wet.gteq1440 <- bbw::recode(var = ehw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ehw.visit <- as.integer(df$ancnow_ehw_visit)
## Number of visits per trimester
ehw.visit.first <- as.integer(df$ancnow_ehw_1tri_times)
ehw.visit.second <- as.integer(df$ancnow_ehw_2tri_times)
ehw.visit.third <- as.integer(df$ancnow_ehw_3tri_times)
## Concatenate ehw provider data.frame
ehw <- data.frame(ehw, ehw.where, ehw.home,
ehw.gov, ehw.private, ehw.srhc,
ehw.village, ehw.eho, ehw.dry,
ehw.dry.lt15, ehw.dry.gteq15lt60,
ehw.dry.gteq60lt120, ehw.dry.gteq120lt360,
ehw.dry.gteq360lt720, ehw.dry.gteq720lt1440,
ehw.dry.gteq1440, ehw.wet,
ehw.wet.lt15, ehw.wet.gteq15lt60,
ehw.wet.gteq60lt120, ehw.wet.gteq120lt360,
ehw.wet.gteq360lt720, ehw.wet.gteq720lt1440,
ehw.wet.gteq1440, ehw.visit,
ehw.visit.first, ehw.visit.second,
ehw.visit.third)
} else {
## Attend ehw
ehw <- as.integer(df$ancpast_who.11)
## Where ehw
ehw.where <- as.integer(df$ancpast_ehw_where)
ehw.home <- bbw::recode(var = ehw.where, recodes = "1=1;NA=NA;else=0")
ehw.gov <- bbw::recode(var = ehw.where, recodes = "2=1;NA=NA;else=0")
ehw.private <- bbw::recode(var = ehw.where, recodes = "3=1;NA=NA;else=0")
ehw.srhc <- bbw::recode(var = ehw.where, recodes = "4=1;NA=NA;else=0")
ehw.village <- bbw::recode(var = ehw.where, recodes = "5=1;NA=NA;else=0")
ehw.eho <- bbw::recode(var = ehw.where, recodes = "6=1;NA=NA;else=0")
## Recode others
## Distance dry season
ehw.dry <- as.integer(df$ancpast_ehw_dist_dry)
ehw.dry.lt15 <- bbw::recode(var = ehw.dry,
recodes = "1=1;NA=NA;else=0")
ehw.dry.gteq15lt60 <- bbw::recode(var = ehw.dry,
recodes = "2=1;NA=NA;else=0")
ehw.dry.gteq60lt120 <- bbw::recode(var = ehw.dry,
recodes = "3=1;NA=NA;else=0")
ehw.dry.gteq120lt360 <- bbw::recode(var = ehw.dry,
recodes = "4=1;NA=NA;else=0")
ehw.dry.gteq360lt720 <- bbw::recode(var = ehw.dry,
recodes = "5=1;NA=NA;else=0")
ehw.dry.gteq720lt1440 <- bbw::recode(var = ehw.dry,
recodes = "6=1;NA=NA;else=0")
ehw.dry.gteq1440 <- bbw::recode(var = ehw.dry,
recodes = "7=1;NA=NA;else=0")
## Distance wet season
ehw.wet <- as.integer(df$ancpast_ehw_dist_wet)
ehw.wet.lt15 <- bbw::recode(var = ehw.wet,
recodes = "1=1;NA=NA;else=0")
ehw.wet.gteq15lt60 <- bbw::recode(var = ehw.wet,
recodes = "2=1;NA=NA;else=0")
ehw.wet.gteq60lt120 <- bbw::recode(var = ehw.wet,
recodes = "3=1;NA=NA;else=0")
ehw.wet.gteq120lt360 <- bbw::recode(var = ehw.wet,
recodes = "4=1;NA=NA;else=0")
ehw.wet.gteq360lt720 <- bbw::recode(var = ehw.wet,
recodes = "5=1;NA=NA;else=0")
ehw.wet.gteq720lt1440 <- bbw::recode(var = ehw.wet,
recodes = "6=1;NA=NA;else=0")
ehw.wet.gteq1440 <- bbw::recode(var = ehw.wet,
recodes = "7=1;NA=NA;else=0")
## Number of visits
ehw.visit <- as.integer(df$ancpast_ehw_visit)
## Number of visits per trimester
ehw.visit.first <- as.integer(df$ancpast_ehw_1tri_times)
ehw.visit.second <- as.integer(df$ancpast_ehw_2tri_times)
ehw.visit.third <- as.integer(df$ancpast_ehw_3tri_times)
## Concatenate ehw provider data.frame
ehw <- data.frame(ehw, ehw.where, ehw.home,
ehw.gov, ehw.private, ehw.srhc,
ehw.village, ehw.eho, ehw.dry,
ehw.dry.lt15, ehw.dry.gteq15lt60,
ehw.dry.gteq60lt120, ehw.dry.gteq120lt360,
ehw.dry.gteq360lt720, ehw.dry.gteq720lt1440,
ehw.dry.gteq1440, ehw.wet,
ehw.wet.lt15, ehw.wet.gteq15lt60,
ehw.wet.gteq60lt120, ehw.wet.gteq120lt360,
ehw.wet.gteq360lt720, ehw.wet.gteq720lt1440,
ehw.wet.gteq1440, ehw.visit,
ehw.visit.first, ehw.visit.second,
ehw.visit.third)
}
## Return data.frame
return(ehw)
}
################################################################################
#
#' Function to recode the personnel type providing antenatal care services for
#' the Myanmar MCCT Programme Evaluation survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data for currently pregnant women
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded antenatal care providers visited for
#' antenatal care
#'
#' @examples
#' ## Recode anc provider for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_provider(df = x, status = "current")
#'
#' ## Recode anc provider for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_provider(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_provider <- function(df, status = NULL) {
## Specialist
specialist <- recode_provider_specialist(df = df, status = status)
## Doctor
doctor <- recode_provider_doctor(df = df, status = status)
## Nurse
nurse <- recode_provider_nurse(df = df, status = status)
## Health assistant
ha <- recode_provider_ha(df = df, status = status)
## Private doctor
pdoc <- recode_provider_pdoc(df = df, status = status)
## Lady health visitor
lhv <- recode_provider_lhv(df = df, status = status)
## Midwife
midwife <- recode_provider_midwife(df = df, status = status)
## Assistant midwife
amw <- recode_provider_amw(df = df, status = status)
## Traditional birth attendant
tba <- recode_provider_tba(df = df, status = status)
## Community health worker
chw <- recode_provider_chw(df = df, status = status)
## Ethnic health worker
ehw <- recode_provider_ehw(df = df, status = status)
## Determine status
if(status == "current") {
## Provider costs?
incurCost <- as.integer(df$ancnow_cost)
## Amount
amountCost <- as.integer(df$ancnow_amount)
## Item cost: transportation
transportCost <- as.integer(df$ancnow_costitem.1)
transportCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, transportCost)
## Item cost: registration fees
registrationCost <- as.integer(df$ancnow_costitem.2)
registrationCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, registrationCost)
## Item cost: medicines
medicineCost <- as.integer(df$ancnow_costitem.3)
medicineCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, medicineCost)
## Item cost: laboratory fees
labCost <- as.integer(df$ancnow_costitem.4)
labCost <- ifelse(is.na(incurCost) | incurCost == 0, NA, labCost)
## Item cost: provider fees
providerCost <- as.integer(df$ancnow_costitem.5)
providerCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, providerCost)
## Item cost: gifts
giftCost <- as.integer(df$ancnow_costitem.6)
giftCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, giftCost)
## Borrow money?
borrow <- as.integer(df$ancnow_borrow)
} else {
## Provider costs?
incurCost <- as.integer(df$ancpast_cost)
## Amount
amountCost <- as.integer(df$ancpast_amount)
## Item cost: transportation
transportCost <- as.integer(df$ancpast_costitem.1)
transportCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, transportCost)
## Item cost: registration fees
registrationCost <- as.integer(df$ancpast_costitem.2)
registrationCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, registrationCost)
## Item cost: medicines
medicineCost <- as.integer(df$ancpast_costitem.3)
medicineCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, medicineCost)
## Item cost: laboratory fees
labCost <- as.integer(df$ancpast_costitem.4)
labCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, labCost)
## Item cost: provider fees
providerCost <- as.integer(df$ancpast_costitem.5)
providerCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, providerCost)
## Item cost: gifts
giftCost <- as.integer(df$ancpast_costitem.6)
giftCost <- ifelse(is.na(incurCost) |
incurCost == 0, NA, giftCost)
## Borrow money?
borrow <- as.integer(df$ancpast_borrow)
}
##
anc1 <- rowSums(cbind(specialist$specialist.visit,
doctor$doctor.visit,
nurse$nurse.visit,
ha$ha.visit,
pdoc$pdoc.visit,
lhv$lhv.visit,
midwife$midwife.visit),
na.rm = TRUE)
anc1 <- bbw::recode(var = anc1,
recodes = "1:hi=1;NA=NA;444=NA;448=NA;888=NA;else=0")
##
anc4 <- rowSums(cbind(specialist$specialist.visit,
doctor$doctor.visit,
nurse$nurse.visit,
ha$ha.visit,
pdoc$pdoc.visit,
lhv$lhv.visit,
midwife$midwife.visit,
amw$amw.visit,
tba$tba.visit,
chw$chw.visit,
ehw$ehw.visit),
na.rm = TRUE)
anc4 <- bbw::recode(var = anc4,
recodes = "4:hi=1;NA=NA;444=NA;448=NA;888=NA;1332=NA;else=0")
## Concatenate provider information to a data.frame
providers <- data.frame(specialist, doctor, nurse, ha, pdoc, lhv,
midwife, amw, tba, chw, ehw, anc1, anc4,
incurCost, amountCost, transportCost, registrationCost,
medicineCost, labCost, providerCost, giftCost, borrow)
## Return data.frame
return(providers)
}
################################################################################
#
#' Function to recode counselling associated with antenatal care for the Myanmar
#' MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded counselling indicators associated with
#' antenatal care
#'
#' @examples
#' ## Recode anc counselling for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_counselling(df = x, status = "current")
#'
#' ## Recode anc counselling for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_counselling(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_counselling <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## MCH book
mchBook <- as.integer(df$ancnow_mchbook)
## Counselling
counsel <- as.integer(df$ancnow_conselling)
## Restrict some foods?
restrict <- as.integer(df$ancnow_restrict)
## Restrict vegetables
restrictVeg <- as.integer(df$ancnow_restrict_item.1)
restrictVeg <- ifelse(is.na(restrict) | restrict == 0, NA, restrictVeg)
## Restrict fruits
restrictFruits <- as.integer(df$ancnow_restrict_item.2)
restrictFruits <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFruits)
## Restrict grains
restrictGrains <- as.integer(df$ancnow_restrict_item.3)
restrictGrains <- ifelse(is.na(restrict) | restrict == 0, NA, restrictGrains)
## Restrict meat
restrictMeat <- as.integer(df$ancnow_restrict_item.4)
restrictMeat <- ifelse(is.na(restrict) | restrict == 0, NA, restrictMeat)
## Restrict fish
restrictFish <- as.integer(df$ancnow_restrict_item.5)
restrictFish <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFish)
## Restrict dairy
restrictDairy <- as.integer(df$ancnow_restrict_item.6)
restrictDairy <- ifelse(is.na(restrict) | restrict == 0, NA, restrictDairy)
## concatenate counselling data.frame
counselling <- data.frame(mchBook, counsel, restrict, restrictVeg,
restrictFruits, restrictGrains, restrictMeat,
restrictFish, restrictDairy)
} else {
## MCH book
mchBook <- as.integer(df$ancpast_mchbook)
## Counselling
counsel <- as.integer(df$ancpast_conselling)
## Restrict some foods?
restrict <- as.integer(df$ancpast_restrict)
## Restrict vegetables
restrictVeg <- as.integer(df$ancpast_restrict_item.1)
restrictVeg <- ifelse(is.na(restrict) | restrict == 0, NA, restrictVeg)
## Restrict fruits
restrictFruits <- as.integer(df$ancpast_restrict_item.2)
restrictFruits <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFruits)
## Restrict grains
restrictGrains <- as.integer(df$ancpast_restrict_item.3)
restrictGrains <- ifelse(is.na(restrict) | restrict == 0, NA, restrictGrains)
## Restrict meat
restrictMeat <- as.integer(df$ancpast_restrict_item.4)
restrictMeat <- ifelse(is.na(restrict) | restrict == 0, NA, restrictMeat)
## Restrict fish
restrictFish <- as.integer(df$ancpast_restrict_item.5)
restrictFish <- ifelse(is.na(restrict) | restrict == 0, NA, restrictFish)
## Restrict dairy
restrictDairy <- as.integer(df$ancpast_restrict_item.6)
restrictDairy <- ifelse(is.na(restrict) | restrict == 0, NA, restrictDairy)
## concatenate counselling data.frame
counselling <- data.frame(mchBook, counsel, restrict, restrictVeg,
restrictFruits, restrictGrains, restrictMeat,
restrictFish, restrictDairy)
}
## Return data.frame
return(counselling)
}
################################################################################
#
#' Function to recode supplementation indicators for antenatal care for the
#' Myanmar MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded supplementation indicators associated with
#' antenatal care
#'
#' @examples
#' ## Recode anc supplementation for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_supplementation(df = x, status = "current")
#'
#' ## Recode anc supplementation for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_supplementation(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_supplementation <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## B1 tablets
b1 <- as.integer(df$ancnow_bone)
b1 <- bbw::recode(var = b1, recodes = "999=0")
## IFA tablets
ifa1 <- as.integer(df$ancnow_rion)
ifa1 <- bbw::recode(var = ifa1, recodes = "999=0")
## IFA - frequency
ifa2 <- as.integer(df$ancnow_iron_freq)
ifa2[ifa2 == 0] <- NA
ifa2[ifa2 == 1 & !is.na(ifa2)] <- (as.integer(df$ancnow_iron_count) * (365 / 12))[ifa2 == 1 & !is.na(ifa2)]
ifa2[ifa2 == 2 & !is.na(ifa2)] <- (as.integer(df$ancnow_iron_count) * ((365/12) / 7))[ifa2 == 2 & !is.na(ifa2)]
ifa2[ifa2 == 3 & !is.na(ifa2)] <- as.integer(df$ancnow_iron_count)[ifa2 == 3 & !is.na(ifa2)]
ifa2 <- floor(ifa2)
ifa2[df$ancnow_rion_length == "1" & !is.na(ifa2)] <- ifa2[df$ancnow_rion_length == "1" & !is.na(ifa2)]
ifa2[df$ancnow_rion_length_oth == "1" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "1" & !is.na(df$ancnow_rion_length_oth)]
ifa2[df$ancnow_rion_length_oth == "2" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "2" & !is.na(df$ancnow_rion_length_oth)] * 2
ifa2[df$ancnow_rion_length_oth == "3" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "3" & !is.na(df$ancnow_rion_length_oth)] * 3
ifa2[df$ancnow_rion_length_oth == "4" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "4" & !is.na(df$ancnow_rion_length_oth)] * 4
ifa2[df$ancnow_rion_length_oth == "5" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "5" & !is.na(df$ancnow_rion_length_oth)] * 5
ifa2[df$ancnow_rion_length_oth == "6" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "6" & !is.na(df$ancnow_rion_length_oth)] * 6
ifa2[df$ancnow_rion_length_oth == "7" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "7" & !is.na(df$ancnow_rion_length_oth)] * 7
ifa2[df$ancnow_rion_length_oth == "8" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "8" & !is.na(df$ancnow_rion_length_oth)] * 8
ifa2[df$ancnow_rion_length_oth == "9" & !is.na(df$ancnow_rion_length_oth)] <- ifa2[df$ancnow_rion_length_oth == "9" & !is.na(df$ancnow_rion_length_oth)] * 9
##
ifa3 <- as.integer(df$ancnow_iron_cost)
ifa3 <- ifelse(ifa3 == 1, as.integer(df$ancnow_iron_amount), ifa3)
ifa3 <- bbw::recode(var = ifa3, recodes = "777=NA;999=NA")
## Government hospital
ifa4a <- as.integer(df$ancnow_iron_source.1)
ifa4a <- ifelse(df$ancnow_iron_source == "", NA, ifa4a)
## EHO clinic
ifa4b <- as.integer(df$ancnow_iron_source.2)
ifa4b <- ifelse(df$ancnow_iron_source == "", NA, ifa4b)
## Private doctor/clinic
ifa4c <- as.integer(df$ancnow_iron_source.3)
ifa4c <- ifelse(df$ancnow_iron_source == "", NA, ifa4c)
## SRHC/RHC
ifa4d <- as.integer(df$ancnow_iron_source.4)
ifa4d <- ifelse(df$ancnow_iron_source == "", NA, ifa4d)
## Routine ANC location in ward/village
ifa4e <- as.integer(df$ancnow_iron_source.5)
ifa4e <- ifelse(df$ancnow_iron_source == "", NA, ifa4e)
} else {
## B1 tablets
b1 <- as.integer(df$ancpast_bone)
b1 <- bbw::recode(var = b1, recodes = "999=0")
## IFA tablets
ifa1 <- as.integer(df$ancpast_rion)
ifa1 <- bbw::recode(var = ifa1, recodes = "999=0")
## IFA - frequency
ifa2 <- as.integer(df$ancpast_iron_freq)
ifa2a <- as.integer(df$ancpast_iron_count)
ifa2a <- bbw::recode(var = ifa2a, recodes = "45:hi=NA")
ifa2[ifa2 == 0] <- NA
ifa2[ifa2 == 1 & !is.na(ifa2)] <- (ifa2a * (365.25 / 12))[ifa2 == 1 & !is.na(ifa2)]
ifa2[ifa2 == 2 & !is.na(ifa2)] <- (ifa2a * ((365.25 / 12) / 7))[ifa2 == 2 & !is.na(ifa2)]
ifa2[ifa2 == 3 & !is.na(ifa2)] <- ifa2a[ifa2 == 3 & !is.na(ifa2)]
ifa2 <- floor(ifa2)
ifa2[df$ancpast_rion_length == "1" & !is.na(ifa2)] <- ifa2[df$ancpast_rion_length == "1" & !is.na(ifa2)]
ifa2[df$ancpast_rion_length_oth == "1" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "1" & !is.na(df$ancpast_rion_length_oth)]
ifa2[df$ancpast_rion_length_oth == "2" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "2" & !is.na(df$ancpast_rion_length_oth)] * 2
ifa2[df$ancpast_rion_length_oth == "3" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "3" & !is.na(df$ancpast_rion_length_oth)] * 3
ifa2[df$ancpast_rion_length_oth == "4" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "4" & !is.na(df$ancpast_rion_length_oth)] * 4
ifa2[df$ancpast_rion_length_oth == "5" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "5" & !is.na(df$ancpast_rion_length_oth)] * 5
ifa2[df$ancpast_rion_length_oth == "6" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "6" & !is.na(df$ancpast_rion_length_oth)] * 6
ifa2[df$ancpast_rion_length_oth == "7" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "7" & !is.na(df$ancpast_rion_length_oth)] * 7
ifa2[df$ancpast_rion_length_oth == "8" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "8" & !is.na(df$ancpast_rion_length_oth)] * 8
ifa2[df$ancpast_rion_length_oth == "9" & !is.na(df$ancpast_rion_length_oth)] <- ifa2[df$ancpast_rion_length_oth == "9" & !is.na(df$ancpast_rion_length_oth)] * 9
##
ifa3 <- as.integer(df$ancpast_iron_cost)
ifa3 <- ifelse(ifa3 == 1, as.integer(df$ancpast_iron_amount), ifa3)
ifa3 <- bbw::recode(var = ifa3, recodes = "444=NA;777=NA;999=NA")
## Government hospital
ifa4a <- as.integer(df$ancpast_iron_source.1)
ifa4a <- ifelse(df$ancpast_iron_source == "", NA, ifa4a)
## EHO clinic
ifa4b <- as.integer(df$ancpast_iron_source.2)
ifa4b <- ifelse(df$ancpast_iron_source == "", NA, ifa4b)
## Private doctor/clinic
ifa4c <- as.integer(df$ancpast_iron_source.3)
ifa4c <- ifelse(df$ancpast_iron_source == "", NA, ifa4c)
## SRHC/RHC
ifa4d <- as.integer(df$ancpast_iron_source.4)
ifa4d <- ifelse(df$ancpast_iron_source == "", NA, ifa4d)
## Routine ANC location in ward/village
ifa4e <- as.integer(df$ancpast_iron_source.5)
ifa4e <- ifelse(df$ancpast_iron_source == "", NA, ifa4e)
}
## concatenate
ancSupp <- data.frame(b1, ifa1, ifa2, ifa3, ifa4a, ifa4b, ifa4c, ifa4d, ifa4e)
## Return
return(ancSupp)
}
################################################################################
#
#' Function to recode testing for infections indicators for antenatal care for
#' the Myanmar MCCT Programme Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#'
#' @return A data.frame of recoded testing for infections associated with
#' antenatal care
#'
#' @examples
#' ## Recode data for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc_testing(df = x, status = "current")
#'
#' ## Recode data for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc_testing(df = x, status = "past")
#'
#' @export
#'
#
################################################################################
recode_anc_testing <- function(df, status = NULL) {
## Determine status
if(status == "current") {
## Tests done
test1 <- suppressWarnings(as.integer(df$ancnow_test_yesno))
test1 <- bbw::recode(var = test1, recodes = "1:4=1;888=1;0=0;999=0;NA=NA")
## Hepatitis B
test2a <- suppressWarnings(as.integer(df$ancnow_test_yesno.1))
test2a <- ifelse(is.na(test1), NA, test2a)
## Hepatitis C
test2b <- suppressWarnings(as.integer(df$ancnow_test_yesno.2))
test2b <- ifelse(is.na(test1), NA, test2b)
## HIV/AIDS
test2c <- suppressWarnings(as.integer(df$ancnow_test_yesno.3))
test2c <- ifelse(is.na(test1), NA, test2c)
## Syphillis
test2d <- suppressWarnings(as.integer(df$ancnow_test_yesno.4))
test2d <- ifelse(is.na(test1), NA, test2d)
## Code for other tests
## Government hospital
test3a <- suppressWarnings(as.integer(df$ancnow_test_where.1))
test3a <- ifelse(is.na(test1), NA, test3a)
## EHO clinic
test3b <- suppressWarnings(as.integer(df$ancnow_test_where.2))
test3b <- ifelse(is.na(test1), NA, test3b)
## Private doctor/clinic
test3c <- suppressWarnings(as.integer(df$ancnow_test_where.3))
test3c <- ifelse(is.na(test1), NA, test3c)
## SRHC/RHC
test3d <- suppressWarnings(as.integer(df$ancnow_test_where.4))
test3d <- ifelse(is.na(test1), NA, test3d)
## Routine ANC location in ward/village
test3e <- suppressWarnings(as.integer(df$ancnow_test_where.5))
test3e <- ifelse(is.na(test1), NA, test3e)
## Code for other locations
## Does test cost?
test4 <- suppressWarnings(as.integer(df$ancnow_test_cost))
test5 <- test4
test4 <- bbw::recode(var = test4, recodes = "1:hi=1;0=0;NA=NA")
} else {
## Tests done
test1 <- suppressWarnings(as.integer(df$ancpast_test_yesno))
test1 <- bbw::recode(var = test1, recodes = "1:4=1;888=1;0=0;999=0;NA=NA")
## Hepatitis B
test2a <- suppressWarnings(as.integer(df$ancpast_test_yesno.1))
test2a <- ifelse(is.na(test1), NA, test2a)
## Hepatitis C
test2b <- suppressWarnings(as.integer(df$ancpast_test_yesno.2))
test2b <- ifelse(is.na(test1), NA, test2b)
## HIV/AIDS
test2c <- suppressWarnings(as.integer(df$ancpast_test_yesno.3))
test2c <- ifelse(is.na(test1), NA, test2c)
## Syphillis
test2d <- suppressWarnings(as.integer(df$ancpast_test_yesno.4))
test2d <- ifelse(is.na(test1), NA, test2d)
## Code for other tests
## Government hospital
test3a <- suppressWarnings(as.integer(df$ancpast_test_where.1))
test3a <- ifelse(is.na(test1), NA, test3a)
## EHO clinic
test3b <- suppressWarnings(as.integer(df$ancpast_test_where.2))
test3b <- ifelse(is.na(test1), NA, test3b)
## Private doctor/clinic
test3c <- suppressWarnings(as.integer(df$ancpast_test_where.3))
test3c <- ifelse(is.na(test1), NA, test3c)
## SRHC/RHC
test3d <- suppressWarnings(as.integer(df$ancpast_test_where.4))
test3d <- ifelse(is.na(test1), NA, test3d)
## Routine ANC location in ward/village
test3e <- suppressWarnings(as.integer(df$ancpast_test_where.5))
test3e <- ifelse(is.na(test1), NA, test3e)
## Code for other locations
## Does test cost?
test4 <- suppressWarnings(as.integer(df$ancpast_test_cost))
test5 <- test4
test4 <- bbw::recode(var = test4, recodes = "1:hi=1;0=0;NA=NA")
}
## Concatenate testing indicators
test <- data.frame(test1, test2a, test2b, test2c, test2d,
test3a, test3b, test3c, test3d, test3e,
test4, test5)
## Return
return(test)
}
################################################################################
#
#' Function to recode antenatal care indicators for the Myanmar MCCT Programme
#' Evaluation Survey
#'
#' @param df A data.frame collected for the Myanmar MCCT Programme Evaluation
#' Study containing antenatal care data
#' @param status A character value indicating whether to recode data of
#' currently pregnant women ("current") or previously pregnant women ("past")
#' @param core.columns A vector of variable names to include in resulting
#'
#' @return A data.frame of recoded antenatal care indicators
#'
#' @examples
#' ## Recode anc indicators for currently pregnant women
#' x <- create_anc(df = anc1, x = hh, y = hhMembers, status = "current")
#' recode_anc(df = x, status = "current")
#'
#' ## Recode anc indicators for non-pregnant women
#' x <- create_anc(df = anc2, x = hh, y = hhMembers, status = "past")
#' recode_anc(df = x, status = "past")
#'
#' @export
#
################################################################################
recode_anc <- function(df,
status = NULL,
core.columns = c("KEY",
"geo_rural",
"geo_state",
"geo_villward",
"sample_component")) {
## Provider
provider <- recode_anc_provider(df = df, status = status)
## Counselling
counselling <- recode_anc_counselling(df = df, status = status)
## Supplementation
supplementation <- recode_anc_supplementation(df = df, status = status)
## Testing
testing <- recode_anc_testing(df = df, status = status)
## Concatenate all ANC indicators
ancDF <- data.frame(df[ , core.columns], provider,
counselling, supplementation, testing)
##
return(ancDF)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.