R/dupbinge.R
In phoebehlam/fhrc: provide fhrc lab with different r scripts
#'report entries with duplicated entries
#'
#'@importFrom magrittr "%>%"
#'
#'@examples dup("/Users/phoebelam/Desktop/clean", "MHS")
#'
#'@export
dupbinge <- function (path, study, visit, exclude) {
filenames = intersect(list.files(path = paste(path, "/", study, sep=""), pattern = study, full.names = TRUE, recursive = TRUE),
list.files(path = paste(path, "/", study, sep=""), pattern = ".csv", full.names = TRUE, recursive = TRUE))
diary = lapply(filenames, read.csv)
d1 <- as.data.frame(diary[[1]]) %>% tail (., -2)
d2 <- as.data.frame(diary[[2]]) %>% tail (., -2)
d3 <- as.data.frame(diary[[3]]) %>% tail (., -2)
d4 <- as.data.frame(diary[[4]]) %>% tail (., -2)
d5 <- as.data.frame(diary[[5]]) %>% tail (., -2)
d6 <- as.data.frame(diary[[6]]) %>% tail (., -2)
d7 <- as.data.frame(diary[[7]]) %>% tail (., -2)
d8 <- as.data.frame(diary[[8]]) %>% tail (., -2)
if (study == "OTR" & visit == 1) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"atschool_yn",
"atschoolhr_text",
"atwork_yn",
"atworkhr_text",
"homework_yn",
"extra.sport_yn",
"tvmovies_yn",
"phone_yn",
"friends_yn",
"family_yn",
"outing_yn",
"music_yn",
"otheract_yn",
"otheract_text",
"homework_hour",
"homework_min",
"extra.sport_hour",
"extra.sport_min",
"tvmovies_hour",
"tvmovies_min",
"phone_hour",
"phone_min",
"friends_hour",
"friends_min",
"family_hour",
"family_min",
"outing_hour",
"outing_min",
"music_hour",
"music_min",
"otheract_hour",
"otheract_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"clean_hour",
"clean_min",
"caresib_hour",
"caresib_min",
"errands_hour",
"errands_min",
"helpsib_hour",
"helpsib_min",
"cook_hour",
"cook_min",
"parentwork_hour",
"parentwork_min",
"famother_hour",
"famother_min",
"gencope1",
"gencope2",
"gencope3",
"gencope4",
"gencope5",
"gencope6",
"gencope7",
"rude_yn",
"ignore_yn",
"punish_yn",
"afraid_yn",
"mean_yn",
"names_yn",
"nodiscrim_yn",
"rude.race",
"rude.class",
"rude.gender",
"rude.other_yn",
"rude.unknown",
"rude.other_text",
"rude.context",
"rude.context.other",
"rude.who",
"rude.who.other",
"rude.cope1",
"rude.cope2",
"rude.cope3",
"rude.cope4",
"rude.cope5",
"rude.cope6",
"rude.cope7",
"rude.cope8",
"ignore.race",
"ignore.class",
"ignore.gender",
"ignore.other_yn",
"ignore.unknown",
"ignore.other_text",
"ignore.context",
"ignore.context.other",
"ignore.who",
"ignore.who.other",
"ignore.cope1",
"ignore.cope2",
"ignore.cope3",
"ignore.cope4",
"ignore.cope5",
"ignore.cope6",
"ignore.cope7",
"ignore.cope8",
"punish.race",
"punish.class",
"punish.gender",
"punish.other_yn",
"punish.unknown",
"punish.other_text",
"punish.context",
"punish.context.other",
"punish.who",
"punish.who.other",
"punish.cope1",
"punish.cope2",
"punish.cope3",
"punish.cope4",
"punish.cope5",
"punish.cope6",
"punish.cope7",
"punish.cope8",
"afraid.race",
"afraid.class",
"afraid.gender",
"afraid.other_yn",
"afraid.unknown",
"afraid.other_text",
"afraid.context",
"afraid.context.other",
"afraid.who",
"afraid.who.other",
"afraid.cope1",
"afraid.cope2",
"afraid.cope3",
"afraid.cope4",
"afraid.cope5",
"afraid.cope6",
"afraid.cope7",
"afraid.cope8",
"mean.race",
"mean.class",
"mean.gender",
"mean.other_yn",
"mean.unknown",
"mean.other_text",
"mean.context",
"mean.context.other",
"mean.who",
"mean.who.other",
"mean.cope1",
"mean.cope2",
"mean.cope3",
"mean.cope4",
"mean.cope5",
"mean.cope6",
"mean.cope7",
"mean.cope8",
"names.race",
"names.class",
"names.gender",
"names.other_yn",
"names.unknown",
"names.other_text",
"names.context",
"names.context.other",
"names.who",
"names.who.other",
"names.cope1",
"names.cope2",
"names.cope3",
"names.cope4",
"names.cope5",
"names.cope6",
"names.cope7",
"names.cope8",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
} else if (study == "OTR" & visit ==2) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"school_hour",
"school_min",
"work_hour",
"work_min",
"homework_hour",
"homework_min",
"extra_hour",
"extra_min",
"relax_hour",
"relax_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"famassist_hour",
"famassist_min",
"rude",
"ignored",
"punished",
"afraidof",
"mean",
"names",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
} else if (study == "OTR" & visit == 3) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"school_hour",
"school_min",
"work_hour",
"work_min",
"homework_hour",
"homework_min",
"extra_hour",
"extra_min",
"relax_hour",
"relax_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"famassist_hour",
"famassist_min",
"rude.yn",
"rude.race",
"rude.class",
"rude.gender",
"ignore.yn",
"ignore.race",
"ignore.class",
"ignore.gender",
"punish.yn",
"punish.race",
"punish.class",
"punish.gender",
"afraid.yn",
"afraid.race",
"afraid.class",
"afraid.gender",
"mean.yn",
"mean.race",
"mean.class",
"mean.gender",
"names.yn",
"names.race",
"names.class",
"names.gender",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
}else if (study == "MHS") {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"id",
"firstname",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text")
}
colnames(d1) <- varnames
colnames(d2) <- varnames
colnames(d3) <- varnames
colnames(d4) <- varnames
colnames(d5) <- varnames
colnames(d6) <- varnames
colnames(d7) <- varnames
if (study == "OTR") {
d8varnames <- c("startdate","enddate","status",
"ipaddress","progress","duration.sec",
"finished","recordeddate","qualtricsid",
"lastname","id","email",
"extref","latitude","longitude",
"channel","language","bedtime.1_1",
"bedtime.2_1","bedtime.3_1","waketime.1_1",
"waketime.2_1","waketime.3_1","numremove",
"remove1.1_1","remove1.2_1","remove1.3_1",
"puton1.1_1","puton1.2_1","puton1.3_1",
"removereason1","remove2.1_1","remove2.2_1",
"remove2.3_1","puton2.1_1","puton2.2_1",
"puton2.3_1","removereason2","remove3.1_1",
"remove3.2_1","remove3.3_1","puton3.1_1",
"puton3.2_1","puton3.3_1","removereason3",
"remove4.1_1","remove4.2_1","remove4.3_1",
"puton4.1_1","puton4.2_1","puton4.3_1",
"removereason4")
} else if (study == "MHS") {
d8varnames <- c("startdate","enddate","status",
"ipaddress","progress","duration.sec",
"finished","recordeddate","qualtricsid",
"id","firstname","email",
"extref","latitude","longitude",
"channel","language","bedtime.1_1",
"bedtime.2_1","bedtime.3_1","waketime.1_1",
"waketime.2_1","waketime.3_1","numremove",
"remove1.1_1","remove1.2_1","remove1.3_1",
"puton1.1_1","puton1.2_1","puton1.3_1",
"removereason1","remove2.1_1","remove2.2_1",
"remove2.3_1","puton2.1_1","puton2.2_1",
"puton2.3_1","removereason2","remove3.1_1",
"remove3.2_1","remove3.3_1","puton3.1_1",
"puton3.2_1","puton3.3_1","removereason3",
"remove4.1_1","remove4.2_1","remove4.3_1",
"puton4.1_1","puton4.2_1","puton4.3_1",
"removereason4", "sum")
}
colnames(d8) <- d8varnames
if (study == "MHS") {
d8 <- dplyr::select(d8, -sum)
janitor::tabyl (d1$id, show_missing_levels = F)
janitor::tabyl (d2$id, show_missing_levels = F)
janitor::tabyl (d3$id, show_missing_levels = F)
janitor::tabyl (d4$id, show_missing_levels = F)
janitor::tabyl (d5$id, show_missing_levels = F)
janitor::tabyl (d6$id, show_missing_levels = F)
janitor::tabyl (d7$id, show_missing_levels = F)
janitor::tabyl (d8$id, show_missing_levels = F) #random names for d8?!
d8 %>% dplyr::mutate (id = as.numeric(as.character(id))) %>%
dplyr::filter (is.na(id)==F) -> d8
}
#blank = na
d1 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d1
d2 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d2
d3 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d3
d4 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d4
d5 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d5
d6 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d6
d7 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d7
d8 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d8
#remove pilot/junk entries and junk/identifying variables
#can we just get these deleted please
if (study == "MHS") {
d1 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d1
d2 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d2
d3 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d3
d4 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d4
d5 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d5
d6 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d6
d7 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d7
d8 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999 & id != "EC") %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d8
} else if (study == "OTR") {
d1 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d1
d2 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d2
d3 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d3
d4 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d4
d5 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d5
d6 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d6
d7 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d7
d8 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999 & id != "EC") %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d8
}
#make id the first column
d1 %>% dplyr::select (id, everything()) -> d1
d2 %>% dplyr::select (id, everything()) -> d2
d3 %>% dplyr::select (id, everything()) -> d3
d4 %>% dplyr::select (id, everything()) -> d4
d5 %>% dplyr::select (id, everything()) -> d5
d6 %>% dplyr::select (id, everything()) -> d6
d7 %>% dplyr::select (id, everything()) -> d7
d8 %>% dplyr::select (id, everything()) -> d8
#add suffix to each diary day
d1 %>% dplyr::rename_all(paste0, "_d1") %>% dplyr::rename (id = id_d1)-> d1
d2 %>% dplyr::rename_all(paste0, "_d2") %>% dplyr::rename (id = id_d2)-> d2
d3 %>% dplyr::rename_all(paste0, "_d3") %>% dplyr::rename (id = id_d3)-> d3
d4 %>% dplyr::rename_all(paste0, "_d4") %>% dplyr::rename (id = id_d4)-> d4
d5 %>% dplyr::rename_all(paste0, "_d5") %>% dplyr::rename (id = id_d5)-> d5
d6 %>% dplyr::rename_all(paste0, "_d6") %>% dplyr::rename (id = id_d6)-> d6
d7 %>% dplyr::rename_all(paste0, "_d7") %>% dplyr::rename (id = id_d7)-> d7
d8 %>% dplyr::rename_all(paste0, "_d8") %>% dplyr::rename (id = id_d8)-> d8
### otr: for handling 1431 only ###
#keeping only the march entries
if (study == "OTR" & visit == 1) {
d1 %>% dplyr::filter (qualtricsid_d1 != "R_eDvHtKkNqsLe9eZ") -> d1
d7 %>% dplyr::filter (qualtricsid_d7 != "R_1MZhUWUmixF3WIl") -> d7
d8 %>% dplyr::filter (qualtricsid_d8 != "R_11ZmpdqJ8kOgjfw" & qualtricsid_d8 != "R_QmRrnCdnJVW3iVz") -> d8
}
# merge all days together
d1 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d1
d2 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d2
d3 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d3
d4 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d4
d5 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d5
d6 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d6
d7 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d7
d8 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d8
janitor::tabyl(d8$id) %>% View()
nonuniqmerge <- function (...){
func <- function(...){
df1 = list(...)[[1]]
df2 = list(...)[[2]]
xxx=merge(..., by=c("id", "count"), all = TRUE)
return(xxx)
}
Reduce(func, list(...))
}
merge(d1, d2, by=c("id", "count")) %>% View()
diary <- nonuniqmerge(d1, d2, d3, d4, d5, d6, d7, d8)
#wide to long
if (study == "OTR") {
diaryl <- data.table::melt (data.table::setDT(dplyr::select(diary, id, matches( c('startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text')))),
measure = patterns( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'),
value.name = c( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'))
} else if (study == "MHS") {
diaryl <- data.table::melt (data.table::setDT(diary),
measure = patterns( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'),
value.name = c( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'))
}
diaryl %>%
arrange (id) %>%
dplyr::rename (qualtrics_day = variable) -> diaryl
# exclude duplicates from descriptive purposes for edith
diaryl %>% dplyr::filter (!id %in% exclude) -> diaryl
# binge alert adding
#put together the bed time and the wake time
diaryl %>%
dplyr::rename (bedtime.hr = bedtime.1_1,
bedtime.min = bedtime.2_1,
bedtime.ampm = bedtime.3_1,
waketime.hr = waketime.1_1,
waketime.min = waketime.2_1,
waketime.ampm = waketime.3_1) -> diaryl
diaryl %>%
dplyr::mutate (bedtime.hr = case_when (as.numeric(bedtime.hr)<10~ paste("0", bedtime.hr, sep=""),
TRUE~ bedtime.hr),
bedtime.min = case_when (as.numeric(bedtime.min)<10~ paste("0", bedtime.min, sep=""),
TRUE~ bedtime.min),
bedtime.ampm = case_when (bedtime.ampm=="1"~ "am",
bedtime.ampm=="2"~ "pm")) -> diaryl
diaryl %>%
dplyr::mutate (waketime.hr = case_when (as.numeric(waketime.hr)<10~ paste("0", waketime.hr, sep=""),
TRUE~ waketime.hr),
waketime.min = case_when (as.numeric(waketime.min)<10~ paste("0", waketime.min, sep=""),
TRUE~ waketime.min),
waketime.ampm = case_when (waketime.ampm=="1"~ "am",
waketime.ampm=="2"~ "pm")) -> diaryl
diaryl %>%
dplyr::mutate (bedtime_raw = case_when (is.na(bedtime.hr)==FALSE~paste(bedtime.hr, ":", bedtime.min, bedtime.ampm, sep=""),
is.na(bedtime.hr)==TRUE~ NA_character_)) %>%
dplyr::mutate (waketime_raw = case_when (is.na(waketime.hr)==FALSE~paste(waketime.hr, ":", waketime.min, waketime.ampm, sep=""),
is.na(waketime.hr)==TRUE~ NA_character_)) -> diaryl
#add sleep ref date based on enddate
# generate the dates for the sleep date participant is reporting about and the date participant reported sleep
# for "inbed.date"= date of sleep participant is reporting about
# if they did it before midnight, then the reported sleep date = qualtrics timestamp date - 1 (because it reference last night)
# if they did it after midnight, then the reported sleep date = qualtrics timestamp date - 2 (because it reference last night and they did it past midnight)
# for "inbed.reportdate" = date participant reported sleep (adjusted)
# if they did it before midnight, then the reported sleep date = qualtrics timestamp date (no adjustment)
# if they did it after midnight, then the reported sleep date = qualtrics timestamp date - 1 (because they did it past midnight)
# using hour < 21 to defined past midnight, because each diary sent at 9pm, so no way they can do it before then for any given day
diaryl %>%
tidyr::separate (enddate, c("qualtrics_date", "qualtrics_time"), " ", fill = "right", remove= FALSE) %>%
dplyr::mutate (qualtrics_time = as.character(qualtrics_time)) %>%
tidyr::separate (qualtrics_time, c("hour", "min", "sec"), ":", fill ="right", remove = FALSE) %>%
dplyr::mutate (hour = as.numeric (as.character(hour))) -> diaryl
diaryl %>%
dplyr::mutate (qualtrics_day = as.numeric(as.character(qualtrics_day))) %>%
dplyr::mutate (inbed.reportdate = case_when (qualtrics_day!=8 & hour < 21 ~ as.Date(qualtrics_date)-1,
qualtrics_day!=8 & hour >= 21~ as.Date(qualtrics_date),
qualtrics_day==8~ as.Date(qualtrics_date))) %>%
dplyr::mutate (inbed.date = case_when (qualtrics_day!=8 & hour < 21 ~ as.Date(qualtrics_date)-2,
qualtrics_day!=8 & hour >= 21 ~ as.Date(qualtrics_date) - 1,
qualtrics_day==8~ as.Date(qualtrics_date) - 1)) %>%
dplyr::mutate (inbed.report.weekday = weekdays(as.Date(inbed.reportdate)),
inbed.weekday = weekdays(as.Date(inbed.date))) -> diaryl
#add binge alert here
#binge defined by two entries indexing the same sleep date
diaryl %>%
arrange (id, qualtrics_day) %>%
dplyr::group_by(id) %>%
dplyr::mutate (inbed.rowdiff = inbed.date - lag(inbed.date),
inbed.rowdiff2 = inbed.date - lead(inbed.date)) %>%
dplyr::mutate (binge = case_when (inbed.rowdiff == 0 | inbed.rowdiff2 == 0 ~ "binge",
is.na(inbed.rowdiff)==TRUE & is.na(inbed.rowdiff2)==TRUE ~ NA_character_,
TRUE ~ "ok")) -> diaryl
# output organizing
# check all days have same # of entries
check1 <- janitor::tabyl (diaryl$qualtrics_day)
# check that everyone has 8 rows (outputting those who don't)
check2 <- janitor::tabyl (diaryl$id, show_missing_levels = F) %>% as.data.frame(.) %>% dplyr::filter (n!=8)
# total number of participants
totp <- janitor::tabyl (diaryl$qualtrics_day, show_missing_levels = F)
# total number of entries of every participants
toten<- diaryl %>%
dplyr::filter (is.na(startdate)==F) %>% nrow()
# total number of participants have at least one entry binged
diaryl %>%
dplyr::group_by(id) %>%
dplyr::mutate (binge_num = case_when(binge == "ok"~ 0,
binge == "binge"~ 1,
TRUE~ NA_real_)) %>%
dplyr::mutate (binge_tot = sum(binge_num, na.rm=T)) %>%
ungroup() %>%
dplyr::mutate (binge_yn = case_when(binge_tot == 0~0,
binge_tot >0~ 1)) -> diaryl
# diaryl %>% dplyr::select (id, inbed.date, inbed.rowdiff, inbed.rowdiff2, qualtrics_day, binge, binge_tot, binge_yn) %>% View ()
diaryl %>% dplyr::filter (qualtrics_day==1) -> temp
bingeyn<- janitor::tabyl (temp$binge_yn)
# binge broke down by number of entries
bingebreak<- janitor::tabyl (temp$binge_tot)
# total number of entries tagged as binge
bingetot <- janitor::tabyl (diaryl$binge)
result <- list("check all days have same # of entries" = check1,
"check that everyone has 8 rows (outputting those who don't)" = check2,
"total number of participants (excluding user inputted ids)"= totp,
"total number of entries of every participants (excluding user inputted ids" = toten,
"total number of participants have at least one entry binged" = bingeyn,
"total number of entries tagged as binge" = bingetot,
"binge broke down by number of entries" = bingebreak)
return (result)
}
phoebehlam/fhrc documentation built on Nov. 10, 2023, 8:31 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.
#'report entries with duplicated entries
#'
#'@importFrom magrittr "%>%"
#'
#'@examples dup("/Users/phoebelam/Desktop/clean", "MHS")
#'
#'@export
dupbinge <- function (path, study, visit, exclude) {
filenames = intersect(list.files(path = paste(path, "/", study, sep=""), pattern = study, full.names = TRUE, recursive = TRUE),
list.files(path = paste(path, "/", study, sep=""), pattern = ".csv", full.names = TRUE, recursive = TRUE))
diary = lapply(filenames, read.csv)
d1 <- as.data.frame(diary[[1]]) %>% tail (., -2)
d2 <- as.data.frame(diary[[2]]) %>% tail (., -2)
d3 <- as.data.frame(diary[[3]]) %>% tail (., -2)
d4 <- as.data.frame(diary[[4]]) %>% tail (., -2)
d5 <- as.data.frame(diary[[5]]) %>% tail (., -2)
d6 <- as.data.frame(diary[[6]]) %>% tail (., -2)
d7 <- as.data.frame(diary[[7]]) %>% tail (., -2)
d8 <- as.data.frame(diary[[8]]) %>% tail (., -2)
if (study == "OTR" & visit == 1) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"atschool_yn",
"atschoolhr_text",
"atwork_yn",
"atworkhr_text",
"homework_yn",
"extra.sport_yn",
"tvmovies_yn",
"phone_yn",
"friends_yn",
"family_yn",
"outing_yn",
"music_yn",
"otheract_yn",
"otheract_text",
"homework_hour",
"homework_min",
"extra.sport_hour",
"extra.sport_min",
"tvmovies_hour",
"tvmovies_min",
"phone_hour",
"phone_min",
"friends_hour",
"friends_min",
"family_hour",
"family_min",
"outing_hour",
"outing_min",
"music_hour",
"music_min",
"otheract_hour",
"otheract_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"clean_hour",
"clean_min",
"caresib_hour",
"caresib_min",
"errands_hour",
"errands_min",
"helpsib_hour",
"helpsib_min",
"cook_hour",
"cook_min",
"parentwork_hour",
"parentwork_min",
"famother_hour",
"famother_min",
"gencope1",
"gencope2",
"gencope3",
"gencope4",
"gencope5",
"gencope6",
"gencope7",
"rude_yn",
"ignore_yn",
"punish_yn",
"afraid_yn",
"mean_yn",
"names_yn",
"nodiscrim_yn",
"rude.race",
"rude.class",
"rude.gender",
"rude.other_yn",
"rude.unknown",
"rude.other_text",
"rude.context",
"rude.context.other",
"rude.who",
"rude.who.other",
"rude.cope1",
"rude.cope2",
"rude.cope3",
"rude.cope4",
"rude.cope5",
"rude.cope6",
"rude.cope7",
"rude.cope8",
"ignore.race",
"ignore.class",
"ignore.gender",
"ignore.other_yn",
"ignore.unknown",
"ignore.other_text",
"ignore.context",
"ignore.context.other",
"ignore.who",
"ignore.who.other",
"ignore.cope1",
"ignore.cope2",
"ignore.cope3",
"ignore.cope4",
"ignore.cope5",
"ignore.cope6",
"ignore.cope7",
"ignore.cope8",
"punish.race",
"punish.class",
"punish.gender",
"punish.other_yn",
"punish.unknown",
"punish.other_text",
"punish.context",
"punish.context.other",
"punish.who",
"punish.who.other",
"punish.cope1",
"punish.cope2",
"punish.cope3",
"punish.cope4",
"punish.cope5",
"punish.cope6",
"punish.cope7",
"punish.cope8",
"afraid.race",
"afraid.class",
"afraid.gender",
"afraid.other_yn",
"afraid.unknown",
"afraid.other_text",
"afraid.context",
"afraid.context.other",
"afraid.who",
"afraid.who.other",
"afraid.cope1",
"afraid.cope2",
"afraid.cope3",
"afraid.cope4",
"afraid.cope5",
"afraid.cope6",
"afraid.cope7",
"afraid.cope8",
"mean.race",
"mean.class",
"mean.gender",
"mean.other_yn",
"mean.unknown",
"mean.other_text",
"mean.context",
"mean.context.other",
"mean.who",
"mean.who.other",
"mean.cope1",
"mean.cope2",
"mean.cope3",
"mean.cope4",
"mean.cope5",
"mean.cope6",
"mean.cope7",
"mean.cope8",
"names.race",
"names.class",
"names.gender",
"names.other_yn",
"names.unknown",
"names.other_text",
"names.context",
"names.context.other",
"names.who",
"names.who.other",
"names.cope1",
"names.cope2",
"names.cope3",
"names.cope4",
"names.cope5",
"names.cope6",
"names.cope7",
"names.cope8",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
} else if (study == "OTR" & visit ==2) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"school_hour",
"school_min",
"work_hour",
"work_min",
"homework_hour",
"homework_min",
"extra_hour",
"extra_min",
"relax_hour",
"relax_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"famassist_hour",
"famassist_min",
"rude",
"ignored",
"punished",
"afraidof",
"mean",
"names",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
} else if (study == "OTR" & visit == 3) {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"lastname",
"id",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text",
"school_hour",
"school_min",
"work_hour",
"work_min",
"homework_hour",
"homework_min",
"extra_hour",
"extra_min",
"relax_hour",
"relax_min",
"clean_yn",
"caresib_yn",
"errands_yn",
"helpsib_yn",
"cook_yn",
"parentwork_yn",
"famother_yn",
"nofamob_yn",
"famother_text",
"famassist_hour",
"famassist_min",
"rude.yn",
"rude.race",
"rude.class",
"rude.gender",
"ignore.yn",
"ignore.race",
"ignore.class",
"ignore.gender",
"punish.yn",
"punish.race",
"punish.class",
"punish.gender",
"afraid.yn",
"afraid.race",
"afraid.class",
"afraid.gender",
"mean.yn",
"mean.race",
"mean.class",
"mean.gender",
"names.yn",
"names.race",
"names.class",
"names.gender",
"overload1",
"overload2",
"overload3",
"overload4",
"complete")
}else if (study == "MHS") {
varnames <- c("startdate",
"enddate",
"status",
"ipaddress",
"progress",
"duration.sec",
"finished",
"recordeddate",
"qualtricsid",
"id",
"firstname",
"email",
"extref",
"latitude",
"longitude",
"channel",
"language",
"bedtime.1_1",
"bedtime.2_1",
"bedtime.3_1",
"waketime.1_1",
"waketime.2_1",
"waketime.3_1",
"numremove",
"remove1.1_1",
"remove1.2_1",
"remove1.3_1",
"puton1.1_1",
"puton1.2_1",
"puton1.3_1",
"removereason1",
"remove2.1_1",
"remove2.2_1",
"remove2.3_1",
"puton2.1_1",
"puton2.2_1",
"puton2.3_1",
"removereason2",
"remove3.1_1",
"remove3.2_1",
"remove3.3_1",
"puton3.1_1",
"puton3.2_1",
"puton3.3_1",
"removereason3",
"remove4.1_1",
"remove4.2_1",
"remove4.3_1",
"puton4.1_1",
"puton4.2_1",
"puton4.3_1",
"removereason4",
"nap",
"sick",
"med_yn",
"med_text")
}
colnames(d1) <- varnames
colnames(d2) <- varnames
colnames(d3) <- varnames
colnames(d4) <- varnames
colnames(d5) <- varnames
colnames(d6) <- varnames
colnames(d7) <- varnames
if (study == "OTR") {
d8varnames <- c("startdate","enddate","status",
"ipaddress","progress","duration.sec",
"finished","recordeddate","qualtricsid",
"lastname","id","email",
"extref","latitude","longitude",
"channel","language","bedtime.1_1",
"bedtime.2_1","bedtime.3_1","waketime.1_1",
"waketime.2_1","waketime.3_1","numremove",
"remove1.1_1","remove1.2_1","remove1.3_1",
"puton1.1_1","puton1.2_1","puton1.3_1",
"removereason1","remove2.1_1","remove2.2_1",
"remove2.3_1","puton2.1_1","puton2.2_1",
"puton2.3_1","removereason2","remove3.1_1",
"remove3.2_1","remove3.3_1","puton3.1_1",
"puton3.2_1","puton3.3_1","removereason3",
"remove4.1_1","remove4.2_1","remove4.3_1",
"puton4.1_1","puton4.2_1","puton4.3_1",
"removereason4")
} else if (study == "MHS") {
d8varnames <- c("startdate","enddate","status",
"ipaddress","progress","duration.sec",
"finished","recordeddate","qualtricsid",
"id","firstname","email",
"extref","latitude","longitude",
"channel","language","bedtime.1_1",
"bedtime.2_1","bedtime.3_1","waketime.1_1",
"waketime.2_1","waketime.3_1","numremove",
"remove1.1_1","remove1.2_1","remove1.3_1",
"puton1.1_1","puton1.2_1","puton1.3_1",
"removereason1","remove2.1_1","remove2.2_1",
"remove2.3_1","puton2.1_1","puton2.2_1",
"puton2.3_1","removereason2","remove3.1_1",
"remove3.2_1","remove3.3_1","puton3.1_1",
"puton3.2_1","puton3.3_1","removereason3",
"remove4.1_1","remove4.2_1","remove4.3_1",
"puton4.1_1","puton4.2_1","puton4.3_1",
"removereason4", "sum")
}
colnames(d8) <- d8varnames
if (study == "MHS") {
d8 <- dplyr::select(d8, -sum)
janitor::tabyl (d1$id, show_missing_levels = F)
janitor::tabyl (d2$id, show_missing_levels = F)
janitor::tabyl (d3$id, show_missing_levels = F)
janitor::tabyl (d4$id, show_missing_levels = F)
janitor::tabyl (d5$id, show_missing_levels = F)
janitor::tabyl (d6$id, show_missing_levels = F)
janitor::tabyl (d7$id, show_missing_levels = F)
janitor::tabyl (d8$id, show_missing_levels = F) #random names for d8?!
d8 %>% dplyr::mutate (id = as.numeric(as.character(id))) %>%
dplyr::filter (is.na(id)==F) -> d8
}
#blank = na
d1 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d1
d2 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d2
d3 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d3
d4 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d4
d5 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d5
d6 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d6
d7 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d7
d8 %>% dplyr::mutate_all(., list(~na_if(.,""))) -> d8
#remove pilot/junk entries and junk/identifying variables
#can we just get these deleted please
if (study == "MHS") {
d1 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d1
d2 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d2
d3 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d3
d4 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d4
d5 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d5
d6 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d6
d7 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d7
d8 %>% dplyr::filter (is.na (id)==FALSE & is.na(firstname) == FALSE, channel != "preview" & id != 9999 & id != "EC") %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, firstname, extref, email, latitude, longitude, language))-> d8
} else if (study == "OTR") {
d1 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d1
d2 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d2
d3 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d3
d4 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d4
d5 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d5
d6 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d6
d7 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999) %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d7
d8 %>% dplyr::filter (is.na (id)==FALSE & is.na(lastname) == FALSE, channel != "preview" & id != 9999 & id != "EC") %>%
dplyr::filter (grepl("TEST", .$id)== FALSE & grepl("hoebe", .$id)== FALSE & grepl("Edith", .$id)== FALSE & grepl("Test", .$id)== FALSE) %>%
dplyr::select (-c(ipaddress, recordeddate, lastname, extref, email, latitude, longitude, language))-> d8
}
#make id the first column
d1 %>% dplyr::select (id, everything()) -> d1
d2 %>% dplyr::select (id, everything()) -> d2
d3 %>% dplyr::select (id, everything()) -> d3
d4 %>% dplyr::select (id, everything()) -> d4
d5 %>% dplyr::select (id, everything()) -> d5
d6 %>% dplyr::select (id, everything()) -> d6
d7 %>% dplyr::select (id, everything()) -> d7
d8 %>% dplyr::select (id, everything()) -> d8
#add suffix to each diary day
d1 %>% dplyr::rename_all(paste0, "_d1") %>% dplyr::rename (id = id_d1)-> d1
d2 %>% dplyr::rename_all(paste0, "_d2") %>% dplyr::rename (id = id_d2)-> d2
d3 %>% dplyr::rename_all(paste0, "_d3") %>% dplyr::rename (id = id_d3)-> d3
d4 %>% dplyr::rename_all(paste0, "_d4") %>% dplyr::rename (id = id_d4)-> d4
d5 %>% dplyr::rename_all(paste0, "_d5") %>% dplyr::rename (id = id_d5)-> d5
d6 %>% dplyr::rename_all(paste0, "_d6") %>% dplyr::rename (id = id_d6)-> d6
d7 %>% dplyr::rename_all(paste0, "_d7") %>% dplyr::rename (id = id_d7)-> d7
d8 %>% dplyr::rename_all(paste0, "_d8") %>% dplyr::rename (id = id_d8)-> d8
### otr: for handling 1431 only ###
#keeping only the march entries
if (study == "OTR" & visit == 1) {
d1 %>% dplyr::filter (qualtricsid_d1 != "R_eDvHtKkNqsLe9eZ") -> d1
d7 %>% dplyr::filter (qualtricsid_d7 != "R_1MZhUWUmixF3WIl") -> d7
d8 %>% dplyr::filter (qualtricsid_d8 != "R_11ZmpdqJ8kOgjfw" & qualtricsid_d8 != "R_QmRrnCdnJVW3iVz") -> d8
}
# merge all days together
d1 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d1
d2 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d2
d3 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d3
d4 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d4
d5 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d5
d6 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d6
d7 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d7
d8 %>% dplyr::group_by (id) %>% dplyr::mutate(count = row_number()) -> d8
janitor::tabyl(d8$id) %>% View()
nonuniqmerge <- function (...){
func <- function(...){
df1 = list(...)[[1]]
df2 = list(...)[[2]]
xxx=merge(..., by=c("id", "count"), all = TRUE)
return(xxx)
}
Reduce(func, list(...))
}
merge(d1, d2, by=c("id", "count")) %>% View()
diary <- nonuniqmerge(d1, d2, d3, d4, d5, d6, d7, d8)
#wide to long
if (study == "OTR") {
diaryl <- data.table::melt (data.table::setDT(dplyr::select(diary, id, matches( c('startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text')))),
measure = patterns( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'),
value.name = c( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'))
} else if (study == "MHS") {
diaryl <- data.table::melt (data.table::setDT(diary),
measure = patterns( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'),
value.name = c( 'startdate',
'enddate',
'status',
'progress',
'duration.sec',
'finished',
'qualtricsid',
'channel',
'bedtime.1_1',
'bedtime.2_1',
'bedtime.3_1',
'waketime.1_1',
'waketime.2_1',
'waketime.3_1',
'numremove',
'remove1.1_1',
'remove1.2_1',
'remove1.3_1',
'puton1.1_1',
'puton1.2_1',
'puton1.3_1',
'removereason1',
'remove2.1_1',
'remove2.2_1',
'remove2.3_1',
'puton2.1_1',
'puton2.2_1',
'puton2.3_1',
'removereason2',
'remove3.1_1',
'remove3.2_1',
'remove3.3_1',
'puton3.1_1',
'puton3.2_1',
'puton3.3_1',
'removereason3',
'remove4.1_1',
'remove4.2_1',
'remove4.3_1',
'puton4.1_1',
'puton4.2_1',
'puton4.3_1',
'removereason4',
'nap',
'sick',
'med_yn',
'med_text'))
}
diaryl %>%
arrange (id) %>%
dplyr::rename (qualtrics_day = variable) -> diaryl
# exclude duplicates from descriptive purposes for edith
diaryl %>% dplyr::filter (!id %in% exclude) -> diaryl
# binge alert adding
#put together the bed time and the wake time
diaryl %>%
dplyr::rename (bedtime.hr = bedtime.1_1,
bedtime.min = bedtime.2_1,
bedtime.ampm = bedtime.3_1,
waketime.hr = waketime.1_1,
waketime.min = waketime.2_1,
waketime.ampm = waketime.3_1) -> diaryl
diaryl %>%
dplyr::mutate (bedtime.hr = case_when (as.numeric(bedtime.hr)<10~ paste("0", bedtime.hr, sep=""),
TRUE~ bedtime.hr),
bedtime.min = case_when (as.numeric(bedtime.min)<10~ paste("0", bedtime.min, sep=""),
TRUE~ bedtime.min),
bedtime.ampm = case_when (bedtime.ampm=="1"~ "am",
bedtime.ampm=="2"~ "pm")) -> diaryl
diaryl %>%
dplyr::mutate (waketime.hr = case_when (as.numeric(waketime.hr)<10~ paste("0", waketime.hr, sep=""),
TRUE~ waketime.hr),
waketime.min = case_when (as.numeric(waketime.min)<10~ paste("0", waketime.min, sep=""),
TRUE~ waketime.min),
waketime.ampm = case_when (waketime.ampm=="1"~ "am",
waketime.ampm=="2"~ "pm")) -> diaryl
diaryl %>%
dplyr::mutate (bedtime_raw = case_when (is.na(bedtime.hr)==FALSE~paste(bedtime.hr, ":", bedtime.min, bedtime.ampm, sep=""),
is.na(bedtime.hr)==TRUE~ NA_character_)) %>%
dplyr::mutate (waketime_raw = case_when (is.na(waketime.hr)==FALSE~paste(waketime.hr, ":", waketime.min, waketime.ampm, sep=""),
is.na(waketime.hr)==TRUE~ NA_character_)) -> diaryl
#add sleep ref date based on enddate
# generate the dates for the sleep date participant is reporting about and the date participant reported sleep
# for "inbed.date"= date of sleep participant is reporting about
# if they did it before midnight, then the reported sleep date = qualtrics timestamp date - 1 (because it reference last night)
# if they did it after midnight, then the reported sleep date = qualtrics timestamp date - 2 (because it reference last night and they did it past midnight)
# for "inbed.reportdate" = date participant reported sleep (adjusted)
# if they did it before midnight, then the reported sleep date = qualtrics timestamp date (no adjustment)
# if they did it after midnight, then the reported sleep date = qualtrics timestamp date - 1 (because they did it past midnight)
# using hour < 21 to defined past midnight, because each diary sent at 9pm, so no way they can do it before then for any given day
diaryl %>%
tidyr::separate (enddate, c("qualtrics_date", "qualtrics_time"), " ", fill = "right", remove= FALSE) %>%
dplyr::mutate (qualtrics_time = as.character(qualtrics_time)) %>%
tidyr::separate (qualtrics_time, c("hour", "min", "sec"), ":", fill ="right", remove = FALSE) %>%
dplyr::mutate (hour = as.numeric (as.character(hour))) -> diaryl
diaryl %>%
dplyr::mutate (qualtrics_day = as.numeric(as.character(qualtrics_day))) %>%
dplyr::mutate (inbed.reportdate = case_when (qualtrics_day!=8 & hour < 21 ~ as.Date(qualtrics_date)-1,
qualtrics_day!=8 & hour >= 21~ as.Date(qualtrics_date),
qualtrics_day==8~ as.Date(qualtrics_date))) %>%
dplyr::mutate (inbed.date = case_when (qualtrics_day!=8 & hour < 21 ~ as.Date(qualtrics_date)-2,
qualtrics_day!=8 & hour >= 21 ~ as.Date(qualtrics_date) - 1,
qualtrics_day==8~ as.Date(qualtrics_date) - 1)) %>%
dplyr::mutate (inbed.report.weekday = weekdays(as.Date(inbed.reportdate)),
inbed.weekday = weekdays(as.Date(inbed.date))) -> diaryl
#add binge alert here
#binge defined by two entries indexing the same sleep date
diaryl %>%
arrange (id, qualtrics_day) %>%
dplyr::group_by(id) %>%
dplyr::mutate (inbed.rowdiff = inbed.date - lag(inbed.date),
inbed.rowdiff2 = inbed.date - lead(inbed.date)) %>%
dplyr::mutate (binge = case_when (inbed.rowdiff == 0 | inbed.rowdiff2 == 0 ~ "binge",
is.na(inbed.rowdiff)==TRUE & is.na(inbed.rowdiff2)==TRUE ~ NA_character_,
TRUE ~ "ok")) -> diaryl
# output organizing
# check all days have same # of entries
check1 <- janitor::tabyl (diaryl$qualtrics_day)
# check that everyone has 8 rows (outputting those who don't)
check2 <- janitor::tabyl (diaryl$id, show_missing_levels = F) %>% as.data.frame(.) %>% dplyr::filter (n!=8)
# total number of participants
totp <- janitor::tabyl (diaryl$qualtrics_day, show_missing_levels = F)
# total number of entries of every participants
toten<- diaryl %>%
dplyr::filter (is.na(startdate)==F) %>% nrow()
# total number of participants have at least one entry binged
diaryl %>%
dplyr::group_by(id) %>%
dplyr::mutate (binge_num = case_when(binge == "ok"~ 0,
binge == "binge"~ 1,
TRUE~ NA_real_)) %>%
dplyr::mutate (binge_tot = sum(binge_num, na.rm=T)) %>%
ungroup() %>%
dplyr::mutate (binge_yn = case_when(binge_tot == 0~0,
binge_tot >0~ 1)) -> diaryl
# diaryl %>% dplyr::select (id, inbed.date, inbed.rowdiff, inbed.rowdiff2, qualtrics_day, binge, binge_tot, binge_yn) %>% View ()
diaryl %>% dplyr::filter (qualtrics_day==1) -> temp
bingeyn<- janitor::tabyl (temp$binge_yn)
# binge broke down by number of entries
bingebreak<- janitor::tabyl (temp$binge_tot)
# total number of entries tagged as binge
bingetot <- janitor::tabyl (diaryl$binge)
result <- list("check all days have same # of entries" = check1,
"check that everyone has 8 rows (outputting those who don't)" = check2,
"total number of participants (excluding user inputted ids)"= totp,
"total number of entries of every participants (excluding user inputted ids" = toten,
"total number of participants have at least one entry binged" = bingeyn,
"total number of entries tagged as binge" = bingetot,
"binge broke down by number of entries" = bingebreak)
return (result)
}
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.