final?
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AG Damsbo
parent
31b9a01498
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6c01fdf887
@ -15,99 +15,33 @@ library(readxl)
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library(dplyr)
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## -----------------------------------------------------------------------------
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## Data
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## Data file load
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## -----------------------------------------------------------------------------
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setwd("/Volumes/Data/toorisky/")
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dta_ls<-list()
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dta_ls[1]<-read_dta("Alle apo Aarhus 2018.dta") %>% filter(VaskDiag==1) %>%
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mutate(treatment=factor(case_when(trombolyse!=2&trombektomi!=2 ~ 0,
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trombolyse==2|trombektomi==2 ~ 1)),
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sex.n=factor(ifelse(as.integer(substr(cpr, start = 10, stop = 10)) %%2 == 0,
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"female", "male"))) %>%
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left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "Patienter"),
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by=c("ForloebID"="forloebid","cpr"="cpr"))
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dta<-read_dta("Alle apo Aarhus 2018.dta") %>% # Defined dataset
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filter(VaskDiag==1) %>%
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mutate(treatment=factor(case_when(trombolyse!=2&trombektomi!=2 ~ 0,
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trombolyse==2|trombektomi==2 ~ 1)),
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sex.n=factor(ifelse(as.integer(substr(cpr, start = 10, stop = 10)) %%2 == 0,
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"female", "male"))) %>%
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left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "Patienter"),
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by=c("ForloebID"="forloebid"))%>%
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left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "3 mdr. opf."),
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by=c("ForloebID"="ForloebID"))%>%
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mutate(cpr=cpr.x,
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ID=ID.x)%>%
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dplyr::select(-starts_with("cpr."))%>%
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dplyr::select(-starts_with("ID."))
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dta_ls[2]<-read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "3 mdr. opf.") # This excludes patients not treated and not candidates, but included by mistake in the register. Manually adjusted.
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## Her mangler filter for kun at inkludere dem, fra baseline
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setwd("/Users/au301842/nottreated/")
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colnames(dta)<-tolower(colnames(dta))
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## -----------------------------------------------------------------------------
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## Data dictionary
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## -----------------------------------------------------------------------------
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icname<-colnames(read.csv("examlpe instrument.csv"))
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dd<-data.frame(matrix(ncol = length(icname))) ## Data frame to collect all
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colnames(dd)<-icname
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## Tilpasses
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## -----------------------------------------------------------------------------
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## -----------------------------------------------------------------------------
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for (i in 1:length(r_lup)){
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dd_i<-data.frame(matrix(ncol = length(icname),nrow = ncol("[["(r_lup,i)))) ## Data frame to collect all
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colnames(dd_i)<-icname ## for easier reading
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## Variable names
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dd_i[1]<-colnames("[["(r_lup,i))
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## Form Name
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dd_i[2]<-names(r_lup)[i]
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## Field Type
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# dd_i[4]<-ifelse(sapply(r_lup[[i]], class)=="factor","radio","text")
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dd_i[4]<-"text"
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## Field Label
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## Using original attributes as field labels
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fl<-lapply(r_lup[[i]], attr, "label")
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for (j in 1:length(fl)){
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fl[[j]]<-ifelse(is.null(fl[[j]]),
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names(fl)[[j]],
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fl[[j]])
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## If no attributes, variable name is used as "placeholder"
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}
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dd_i[5]<-unlist(fl)
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## Choices
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# for (j in 1:ncol(r_lup[[i]])){
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# if (is.factor(r_lup[[i]][[j]])){
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# lvl<-levels(r_lup[[i]][[j]])
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# lvl_ch<-paste("1,",lvl[1])
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# for (k in 2:length(lvl)){
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# lvl_ch<-c(paste0(lvl_ch," | ",k,", ",lvl[k]))
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# }
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# dd_i[j,6]<-lvl_ch
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# }
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# }
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## Text Validation
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## Only used for date and time data
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# for (j in 1:ncol(r_lup[[i]])){
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# dd_i[j,8]<-case_when(class(r_lup[[i]][[j]])[1]%in%c("POSIXct","POSIXt") ~"datetime_seconds_ymd",
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# class(r_lup[[i]][[j]])[1]%in%c("Date") ~"date_ymd")
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# }
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## Merge all
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dd<-rbind(dd,dd_i)
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if (exp_out){
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# dir.create(file.path("/Volumes/Data/REDCap/data",names(r_lup)[[i]]))
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write.csv(r_lup[[i]],paste0("/Volumes/Data/REDCap/data/",names(r_lup)[[i]],".csv"),row.names = FALSE)
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}
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}
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## -----------------------------------------------------------------------------
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## REDCap pull
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## Fix missing record_id's for upload
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## -----------------------------------------------------------------------------
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## REDCap pull with minimum data
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token=names(suppressWarnings(read.csv("/Users/au301842/nottreated_redcap_token.csv",colClasses = "character")))
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uri="https://redcap.au.dk/api/"
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@ -115,11 +49,51 @@ library(REDCapR)
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redcap <- redcap_read_oneshot(
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redcap_uri = uri,
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token = token
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token = token,
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fields = c("record_id","forloebid")
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)$data
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## Joining and adding record_id's
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dta<-full_join(dta,redcap)
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n_na<-length(dta$record_id[is.na(dta$record_id)])
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n_id<-max(dta$record_id,na.rm=T)
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# filter(!is.na(akut_ind))%>%
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dta$record_id[is.na(dta$record_id)]<-(n_id+1):(n_id+n_na) # Simple math
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## -----------------------------------------------------------------------------
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## Data preparation
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## Data dictionary
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## -----------------------------------------------------------------------------
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setwd("/Users/au301842/nottreated/")
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icname<-colnames(read.csv("examlpe instrument.csv"))
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dd<-data.frame(matrix(ncol = length(icname),
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nrow=ncol(dta))) ## Data frame to collect all
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colnames(dd)<-icname
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## Variable names
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dd[1]<-colnames(dta)
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## Form Name
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dd[2]<-"ddsc"
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## Field Type
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# dd_i[4]<-ifelse(sapply(r_lup[[i]], class)=="factor","radio","text")
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dd[4]<-"text"
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dd[5]<-colnames(dta)
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## -----------------------------------------------------------------------------
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## Instrument file
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## -----------------------------------------------------------------------------
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write.csv(dd,"ddsc_instrument.csv",row.names = FALSE,na="")
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## -----------------------------------------------------------------------------
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## Dataset export
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## -----------------------------------------------------------------------------
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write.csv(dta,"ddsc_dataset.csv",row.names = FALSE)
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