R/recode.r
In mmparker/to1check: Reporting and quality checks for TBESC TO 1 data
Defines functions
recode
Documented in
recode
#' Recodes DMS extract variables for ease of use.
#'
#' This function recodes DMS extract variables for ease of use; that includes
#' \itemize{
#' \item Converting numeric codes into human-readable values;
#' \item Creating strictly-numeric versions of QFT and
#' TSPOT quantitative results
#' \item Creating strictly-numeric versions of QFT and
#' }
#'
#' The input of this function should generally be the output of
#' the \code{\link{convert}} function, and is only meant to be used internally
#' by \code{\link{clean_to1}}
#'
#' @param converted The output of the \code{\link{convert}} function.
recode <- function(converted) {
# Create these variables so R CMD CHECK doesn't think they're globals
AgeAtEnrollment <- Months <- NA
# Keep the originals for comparison
recoded <- converted
############################################################################
# Convert months of age to fractional years
############################################################################
# If there is no entry in AgeAtEnrollment but there is one in Months,
# divide by 12
recoded$preenrollment <- transform(recoded$preenrollment,
AgeAtEnrollment = ifelse(is.na(AgeAtEnrollment) & !is.na(Months),
yes = as.numeric(Months) / 12,
no = AgeAtEnrollment)
)
############################################################################
# Convert test results from numeric to text
############################################################################
recoded$skintest$result[recoded$skintest$result %in% 1] <- "Positive"
recoded$skintest$result[recoded$skintest$result %in% 2] <- "Negative"
recoded$qft$result[recoded$qft$result %in% 1] <- "Positive"
recoded$qft$result[recoded$qft$result %in% 2] <- "Negative"
recoded$qft$result[recoded$qft$result %in% 3] <- "Indeterminate"
recoded$qft$result[recoded$qft$result %in% 2] <- "Failed"
recoded$tspot$result[recoded$tspot$result %in% 1] <- "Positive"
recoded$tspot$result[recoded$tspot$result %in% 2] <- "Negative"
recoded$tspot$result[recoded$tspot$result %in% 3] <- "Borderline"
recoded$tspot$result[recoded$tspot$result %in% 4] <- "Invalid"
recoded$tspot$result[recoded$tspot$result %in% 5] <- "Test Not Performed"
recoded$tspot$result[recoded$tspot$result %in% 6] <- "Test Not Performed"
# Reruns, too
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 1] <- "Positive"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 2] <- "Negative"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 3] <- "Indeterminate"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 2] <- "Failed"
############################################################################
# Create strictly-numeric recodes of the QFT and TSPOT results
############################################################################
resultToNumeric <- function(x) {
as.numeric(gsub(x = x, pattern = ">", replacement = ""))
}
# QFTs
recoded$qft$nil.num <- resultToNumeric(recoded$qft$nil)
recoded$qft$tb.num <- resultToNumeric(recoded$qft$tb)
recoded$qft$mito.num <- resultToNumeric(recoded$qft$mito)
recoded$qft$tbnil.num <- resultToNumeric(recoded$qft$tbnil)
recoded$qft$mitnil.num <- resultToNumeric(recoded$qft$mitnil)
# TSPOTs
recoded$tspot$nil.num <- resultToNumeric(recoded$tspot$nil)
recoded$tspot$mito.num <- resultToNumeric(recoded$tspot$mito)
recoded$tspot$panel_a.num <- resultToNumeric(recoded$tspot$panel_a)
recoded$tspot$panel_b.num <- resultToNumeric(recoded$tspot$panel_b)
# Calculate TB - Nil for TSPOT
recoded$tspot$tbnil.a <- recoded$tspot$panel_a.num - recoded$tspot$nil.num
recoded$tspot$tbnil.b <- recoded$tspot$panel_b.num - recoded$tspot$nil.num
recoded$tspot$tbnil.max <- pmax(recoded$tspot$tbnil.a,
recoded$tspot$tbnil.b)
# Rerun QFTs
recoded$qft$rerun_nil.num <- resultToNumeric(recoded$qft$rerun_nil)
recoded$qft$rerun_tb.num <- resultToNumeric(recoded$qft$rerun_tb)
recoded$qft$rerun_mito.num <- resultToNumeric(recoded$qft$rerun_mito)
recoded$qft$rerun_tbnil.num <- resultToNumeric(recoded$qft$rerun_tbnil)
recoded$qft$rerun_mitnil.num <- resultToNumeric(recoded$qft$rerun_mitnil)
############################################################################
# Participant CloseReason
############################################################################
recoded$master$CloseReason[recoded$master$CloseReason %in% 1] <-
"Triple Negative"
recoded$master$CloseReason[recoded$master$CloseReason %in% 2] <-
"Not eligible"
recoded$master$CloseReason[recoded$master$CloseReason %in% 3] <-
"FU Completed or Lost"
recoded$master$CloseReason[recoded$master$CloseReason %in% 4] <-
"Developed TB Disease"
recoded$master$CloseReason[recoded$master$CloseReason %in% 5] <-
"Died"
recoded$master$CloseReason[recoded$master$CloseReason %in% 6] <-
"Withdrew"
recoded$master$CloseReason[recoded$master$CloseReason %in% 7] <-
"Didn't complete enrollment"
recoded$master$CloseReason[recoded$master$CloseReason %in% NA] <-
"Open"
############################################################################
# Convert country of birth codes from ISO 3166-1 alpha-3 to, you know,
# something humans can actually read
############################################################################
# Use factor() to relabel BirthCountry, then convert back to character
# Uses the to1check package's internal abbreviation -> name dictionary,
# country_codes
recoded$master$BirthCountry <- as.character(
factor(recoded$master$BirthCountry,
levels = country_codes$code,
labels = country_codes$name)
)
############################################################################
# Recode BCG status
############################################################################
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 1] <- "Yes"
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 0] <- "No"
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 99] <- "Don't Know/Refused"
############################################################################
# Treatment plan variables
############################################################################
# Offer, Accept, Complete to logical
recoded$ltbi$OfferTreatment <- as.logical(recoded$ltbi$OfferTreatment)
recoded$ltbi$AcceptTreatment <- as.logical(recoded$ltbi$AcceptTreatment)
recoded$ltbi$TreatmentComplete <- as.logical(recoded$ltbi$TreatmentComplete)
# Treatment Administration Type
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 1] <- "DOPT"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 2] <- "Self-administered"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 3] <- "Combination of DOPT and self-administered"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 4] <- "Unknown"
# Reason not completed
recoded$ltbi$ReasonNotComplete <-
as.character(factor(recoded$ltbi$ReasonNotComplete,
levels = 1:8,
labels = c("Lost to follow-up",
"Refused",
"Moved",
"Diagnosed with active TB",
"Side effects of treatment",
"Pregnancy",
"Died",
"Other")
)
)
# Drug flag to logical
recoded$ltbi$Isoniazid <- !is.na(recoded$ltbi$Isoniazid)
recoded$ltbi$Rifampin <- !is.na(recoded$ltbi$Rifampin)
recoded$ltbi$Rifapentine <- !is.na(recoded$ltbi$Rifapentine)
recoded$ltbi$Other <- !is.na(recoded$ltbi$Other)
# Convert dose frequency variables
freq.recode <- function(x) {
as.character(factor(x,
levels = 1:5,
labels = c("Daily",
"1 x week",
"2 x week",
"3 x week",
"Other")
)
)
}
recoded$ltbi$IsoniazidFreq <- freq.recode(recoded$ltbi$IsoniazidFreq)
recoded$ltbi$RifampinFreq <- freq.recode(recoded$ltbi$RifampinFreq)
recoded$ltbi$RifapentineFreq <- freq.recode(recoded$ltbi$RifapentineFreq)
recoded$ltbi$OtherFreq <- freq.recode(recoded$ltbi$OtherFreq)
# Classify treatment plans
recoded$ltbi$plan[recoded$ltbi$AcceptTreatment] <- "Unknown"
# Daily INH
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "Daily"] <- "Daily INH"
recoded$ltbi$plan[!recoded$ltbi$Isoniazid &
recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$RifampinFreq %in% "Daily"] <- "Daily RIF"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "1 x week" &
recoded$ltbi$RifapentineFreq %in% "1 x week"] <-
"Weekly INH/Rifapentine"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "2 x week"] <-
"Twice-weekly INH"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$RifampinFreq %in% "Daily" &
recoded$ltbi$IsoniazidFreq %in% "Daily"] <-
"Daily Rifamate"
# count(recoded$ltbi[c("Isoniazid", "IsoniazidFreq",
# "Rifampin", "RifampinFreq",
# "Rifapentine", "RifapentineFreq",
# "Other", "OtherFreq",
# "plan")])
############################################################################
# Return the recoded results
############################################################################
recoded
}
mmparker/to1check documentation built on May 23, 2019, 5:05 a.m.
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Defines functions recode
Documented in recode
#' Recodes DMS extract variables for ease of use.
#'
#' This function recodes DMS extract variables for ease of use; that includes
#' \itemize{
#' \item Converting numeric codes into human-readable values;
#' \item Creating strictly-numeric versions of QFT and
#' TSPOT quantitative results
#' \item Creating strictly-numeric versions of QFT and
#' }
#'
#' The input of this function should generally be the output of
#' the \code{\link{convert}} function, and is only meant to be used internally
#' by \code{\link{clean_to1}}
#'
#' @param converted The output of the \code{\link{convert}} function.
recode <- function(converted) {
# Create these variables so R CMD CHECK doesn't think they're globals
AgeAtEnrollment <- Months <- NA
# Keep the originals for comparison
recoded <- converted
############################################################################
# Convert months of age to fractional years
############################################################################
# If there is no entry in AgeAtEnrollment but there is one in Months,
# divide by 12
recoded$preenrollment <- transform(recoded$preenrollment,
AgeAtEnrollment = ifelse(is.na(AgeAtEnrollment) & !is.na(Months),
yes = as.numeric(Months) / 12,
no = AgeAtEnrollment)
)
############################################################################
# Convert test results from numeric to text
############################################################################
recoded$skintest$result[recoded$skintest$result %in% 1] <- "Positive"
recoded$skintest$result[recoded$skintest$result %in% 2] <- "Negative"
recoded$qft$result[recoded$qft$result %in% 1] <- "Positive"
recoded$qft$result[recoded$qft$result %in% 2] <- "Negative"
recoded$qft$result[recoded$qft$result %in% 3] <- "Indeterminate"
recoded$qft$result[recoded$qft$result %in% 2] <- "Failed"
recoded$tspot$result[recoded$tspot$result %in% 1] <- "Positive"
recoded$tspot$result[recoded$tspot$result %in% 2] <- "Negative"
recoded$tspot$result[recoded$tspot$result %in% 3] <- "Borderline"
recoded$tspot$result[recoded$tspot$result %in% 4] <- "Invalid"
recoded$tspot$result[recoded$tspot$result %in% 5] <- "Test Not Performed"
recoded$tspot$result[recoded$tspot$result %in% 6] <- "Test Not Performed"
# Reruns, too
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 1] <- "Positive"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 2] <- "Negative"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 3] <- "Indeterminate"
recoded$qft$rerun_result[recoded$qft$rerun_result %in% 2] <- "Failed"
############################################################################
# Create strictly-numeric recodes of the QFT and TSPOT results
############################################################################
resultToNumeric <- function(x) {
as.numeric(gsub(x = x, pattern = ">", replacement = ""))
}
# QFTs
recoded$qft$nil.num <- resultToNumeric(recoded$qft$nil)
recoded$qft$tb.num <- resultToNumeric(recoded$qft$tb)
recoded$qft$mito.num <- resultToNumeric(recoded$qft$mito)
recoded$qft$tbnil.num <- resultToNumeric(recoded$qft$tbnil)
recoded$qft$mitnil.num <- resultToNumeric(recoded$qft$mitnil)
# TSPOTs
recoded$tspot$nil.num <- resultToNumeric(recoded$tspot$nil)
recoded$tspot$mito.num <- resultToNumeric(recoded$tspot$mito)
recoded$tspot$panel_a.num <- resultToNumeric(recoded$tspot$panel_a)
recoded$tspot$panel_b.num <- resultToNumeric(recoded$tspot$panel_b)
# Calculate TB - Nil for TSPOT
recoded$tspot$tbnil.a <- recoded$tspot$panel_a.num - recoded$tspot$nil.num
recoded$tspot$tbnil.b <- recoded$tspot$panel_b.num - recoded$tspot$nil.num
recoded$tspot$tbnil.max <- pmax(recoded$tspot$tbnil.a,
recoded$tspot$tbnil.b)
# Rerun QFTs
recoded$qft$rerun_nil.num <- resultToNumeric(recoded$qft$rerun_nil)
recoded$qft$rerun_tb.num <- resultToNumeric(recoded$qft$rerun_tb)
recoded$qft$rerun_mito.num <- resultToNumeric(recoded$qft$rerun_mito)
recoded$qft$rerun_tbnil.num <- resultToNumeric(recoded$qft$rerun_tbnil)
recoded$qft$rerun_mitnil.num <- resultToNumeric(recoded$qft$rerun_mitnil)
############################################################################
# Participant CloseReason
############################################################################
recoded$master$CloseReason[recoded$master$CloseReason %in% 1] <-
"Triple Negative"
recoded$master$CloseReason[recoded$master$CloseReason %in% 2] <-
"Not eligible"
recoded$master$CloseReason[recoded$master$CloseReason %in% 3] <-
"FU Completed or Lost"
recoded$master$CloseReason[recoded$master$CloseReason %in% 4] <-
"Developed TB Disease"
recoded$master$CloseReason[recoded$master$CloseReason %in% 5] <-
"Died"
recoded$master$CloseReason[recoded$master$CloseReason %in% 6] <-
"Withdrew"
recoded$master$CloseReason[recoded$master$CloseReason %in% 7] <-
"Didn't complete enrollment"
recoded$master$CloseReason[recoded$master$CloseReason %in% NA] <-
"Open"
############################################################################
# Convert country of birth codes from ISO 3166-1 alpha-3 to, you know,
# something humans can actually read
############################################################################
# Use factor() to relabel BirthCountry, then convert back to character
# Uses the to1check package's internal abbreviation -> name dictionary,
# country_codes
recoded$master$BirthCountry <- as.character(
factor(recoded$master$BirthCountry,
levels = country_codes$code,
labels = country_codes$name)
)
############################################################################
# Recode BCG status
############################################################################
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 1] <- "Yes"
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 0] <- "No"
recoded$medicalhistory$BcgVaccine[recoded$medicalhistory$BcgVaccine
%in% 99] <- "Don't Know/Refused"
############################################################################
# Treatment plan variables
############################################################################
# Offer, Accept, Complete to logical
recoded$ltbi$OfferTreatment <- as.logical(recoded$ltbi$OfferTreatment)
recoded$ltbi$AcceptTreatment <- as.logical(recoded$ltbi$AcceptTreatment)
recoded$ltbi$TreatmentComplete <- as.logical(recoded$ltbi$TreatmentComplete)
# Treatment Administration Type
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 1] <- "DOPT"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 2] <- "Self-administered"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 3] <- "Combination of DOPT and self-administered"
recoded$ltbi$TreatmentAdmin[recoded$ltbi$TreatmentAdmin
%in% 4] <- "Unknown"
# Reason not completed
recoded$ltbi$ReasonNotComplete <-
as.character(factor(recoded$ltbi$ReasonNotComplete,
levels = 1:8,
labels = c("Lost to follow-up",
"Refused",
"Moved",
"Diagnosed with active TB",
"Side effects of treatment",
"Pregnancy",
"Died",
"Other")
)
)
# Drug flag to logical
recoded$ltbi$Isoniazid <- !is.na(recoded$ltbi$Isoniazid)
recoded$ltbi$Rifampin <- !is.na(recoded$ltbi$Rifampin)
recoded$ltbi$Rifapentine <- !is.na(recoded$ltbi$Rifapentine)
recoded$ltbi$Other <- !is.na(recoded$ltbi$Other)
# Convert dose frequency variables
freq.recode <- function(x) {
as.character(factor(x,
levels = 1:5,
labels = c("Daily",
"1 x week",
"2 x week",
"3 x week",
"Other")
)
)
}
recoded$ltbi$IsoniazidFreq <- freq.recode(recoded$ltbi$IsoniazidFreq)
recoded$ltbi$RifampinFreq <- freq.recode(recoded$ltbi$RifampinFreq)
recoded$ltbi$RifapentineFreq <- freq.recode(recoded$ltbi$RifapentineFreq)
recoded$ltbi$OtherFreq <- freq.recode(recoded$ltbi$OtherFreq)
# Classify treatment plans
recoded$ltbi$plan[recoded$ltbi$AcceptTreatment] <- "Unknown"
# Daily INH
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "Daily"] <- "Daily INH"
recoded$ltbi$plan[!recoded$ltbi$Isoniazid &
recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$RifampinFreq %in% "Daily"] <- "Daily RIF"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "1 x week" &
recoded$ltbi$RifapentineFreq %in% "1 x week"] <-
"Weekly INH/Rifapentine"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
!recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$IsoniazidFreq %in% "2 x week"] <-
"Twice-weekly INH"
recoded$ltbi$plan[recoded$ltbi$Isoniazid &
recoded$ltbi$Rifampin &
!recoded$ltbi$Rifapentine &
!recoded$ltbi$Other &
recoded$ltbi$RifampinFreq %in% "Daily" &
recoded$ltbi$IsoniazidFreq %in% "Daily"] <-
"Daily Rifamate"
# count(recoded$ltbi[c("Isoniazid", "IsoniazidFreq",
# "Rifampin", "RifampinFreq",
# "Rifapentine", "RifapentineFreq",
# "Other", "OtherFreq",
# "plan")])
############################################################################
# Return the recoded results
############################################################################
recoded
}
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