Creating new = variables from messy data in multiple variables - r

Question

I am busy data cleaning a TB drug register. I have already done it in stata but would like to move across to R (and improve the new variables slightly).
There are 5 variables that describe each drug regimen,
drugname1, drugstartdate1, drugenddate1, drugdose1 (ie."500"), drugunit1 (ie."mg"). Numbers go up to 60 so I know I may need to make use of looping in one form or another.
The drugname1 is not standardised to one specific drug, so bedaquiline (bdq) can be in drugname1 or drugname2 or drugname50.
At the end of the day I would like to have variables that relate to a specific drug, for instance (bedaquiline = bdq:
onbdq bdqstartdate bdqenddate bdqdose
*there may also be patients who start on bdq, then stop, then start again so something along the lines of
onbdq1 bdqstartdate1 bdqenddate1 bdqdose1 onbdq2 bdqstartdate2 bdqenddate2 bdqdose2 would be more accurate.
#Essentially, I have this:
mre <- as.data.frame(structure(list(drugname1 = c("Bedaquiline", "Bedaquiline", "Bedaquiline",
NA, "Amikacin"), drugstartdate1 = structure(c(18875, 18383, 18795,
NA, 16743), class = "Date"), drugenddate1 = structure(c(NA, NA,
18808, NA, NA), class = "Date"), drugdose1 = c(NA, "400", "200",
NA, NA), drugunit1 = c(NA, "mg", "mg", NA, NA), drugname2 = c("Levofloxacin",
"Levofloxacin", "Levofloxacin", "p-Aminosalicylic Acid", "Terizidone"
), drugstartdate2 = structure(c(18875, 18383, 18795, 16709, 16743
), class = "Date"), drugenddate2 = structure(c(NA, NA, 19139,
NA, NA), class = "Date"), drugdose2 = c(NA, "750", "1000", NA,
NA), drugunit2 = c(NA, "mg", "mg", "mg", NA), drugname3 = c("Linezolid",
"Linezolid", "Linezolid", "Ethionamide", "Ethambutol"), drugstartdate3 = structure(c(18875,
18383, 18795, 16709, 16743), class = "Date"), drugenddate3 = structure(c(NA,
18438, 19139, NA, NA), class = "Date"), drugdose3 = c(NA, "600",
"600", NA, NA), drugunit3 = c(NA, "mg", "mg", "mg", NA)), row.names = c(NA,
5L), class = "data.frame"))
#and I want something like this for each drug (bedaquiline = bdq) and so on:
output <- as.data.frame(structure(list(
onbdq = c(TRUE, TRUE),
bdqtartdate = structure(c(18875, 18383 ), class= "Date"),
bdqenddate = structure(c(NA, NA), class = "Date"),
bdqdose = structure(c(NA, "200mg")))))
Some starting points have been
library(dplyr)
#combing drugdose and drugunit into variable dose
EDRsub <- mutate(EDRsub, dose1= paste0(drugdose1, drugunit1))
#but I am unsure of how to go about looping, in my head this should work:
for(i in 1:3){
mre <- mutate(mre, paste0(dose,i) = paste0(drugdose,i,drugunit,i))
}
#or
for(i in 1:3){
mre <- mutate(mre, dose[[i]]) = (drugdose[[i]],drugunit[[i]])
}
but neither do. There is clearly something fundamental I am not cracking with the R syntax.
# I also had a go at reshaping with mixed results, coding is going through, but it seems clunky and inefficient aswell as not quite giving me what I want.
long <- mre %>%
pivot_longer(
cols = starts_with(c("drugname")),
names_to = "observation",
names_patter = "new_?(.*)",
values_to = c("drugname"),
values_drop_na = TRUE
) %>%
pivot_longer(
cols = starts_with(c("as.character(drugstartdate)")),
names_to = "observationdrugstartdate",
names_patter = "new_?(.*)",
values_to = c("drugstartdate"),
values_drop_na = TRUE
) %>%
distinct()
I have tried bits and pieces of code but generally feel as though I have thrown myself in the middle of the atlantic. I am struggling converting looping and reshaping knowledge from stata and at the same time feel like R has a better way of doing things where the logic of stata (which I am used to) is not being helpful.
This is some of the code statalist came up with : https://www.statalist.org/forums/forum/general-stata-discussion/general/1680179-forvalues-%60i-1%60-and-wide-to-long-dataset
But isn't exactly what I am after with this question.
Any advice on coding is welcome as well as suggestions for how to arrange the data in the "R" way.