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redcap_cases_count.R
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redcap_cases_count.R
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library(tidyverse)
data_prefinal <- read_csv("redcap_export.csv",
na = c("NA", "NASK", "INV", "NAVU", "ASKU"),
col_types= cols(birthday = col_date("%Y-%m-%d"), psycho_date = col_date("%Y-%m-%d")),
guess_max=12345)
#tidy data
##tag branch of data (SCG = arm_1, ASA/SET = arm_2, CIS/FEMS = arm_4)
data_prefinal$redcap_branch <- str_sub(data_prefinal$redcap_event_name, -5)
##filling demogrpahics info to all records
data_prefinal_01a <- filter(data_prefinal, redcap_branch != "arm_5")
data_prefinal_02a <- filter(data_prefinal, redcap_branch == "arm_5" & (is.na(redcap_repeat_instance) == T))
data_prefinal_02a <- select(data_prefinal_02a, record_id, surname, firstname, birthday, sex, later_hand)
data_prefinal_02b <- filter(data_prefinal, redcap_branch == "arm_5" & (is.na(redcap_repeat_instance) != T))
data_prefinal_02b <- select(data_prefinal_02b, -surname, -firstname, -birthday, -sex, -later_hand)
data_final_02 <- left_join(data_prefinal_02b, data_prefinal_02a, by=c("record_id"), multiple = "all", keep = F)
data_prefinal_01 <-
tibble(record_id = data_prefinal_01a$record_id,
redcap_branch = data_prefinal_01a$redcap_branch,
redcap_repeat_instrument = data_prefinal_01a$redcap_repeat_instrument,
redcap_repeat_instance = data_prefinal_01a$redcap_repeat_instance,
firstname = data_prefinal_01a$firstname,
surname = data_prefinal_01a$surname,
birthday = data_prefinal_01a$birthday,
sex = data_prefinal_01a$sex,
later_hand = data_prefinal_01a$later_hand,
basic_demographic_data_complete = data_prefinal_01a$basic_demographic_data_complete,
) %>%
filter(is.na(data_prefinal_01a$basic_demographic_data_complete)!=T) %>%
left_join(data_prefinal_01a, by=c("record_id", "redcap_branch"), keep = F)
data_final_01 <- select(data_prefinal_01,
-redcap_repeat_instrument.y,
-redcap_repeat_instance.y,
-firstname.y,
-surname.y,
-birthday.y,
-sex.y,
-later_hand.y,
-basic_demographic_data_complete.y)
data_final_01 <- rename(data_final_01,
redcap_repeat_instrument = redcap_repeat_instrument.x,
redcap_repeat_instance = redcap_repeat_instance.x,
firstname = firstname.x,
surname = surname.x,
birthday = birthday.x,
sex = sex.x,
later_hand = later_hand.x,
basic_demographic_data_complete = basic_demographic_data_complete.x)
data_final <- rbind(data_final_01, data_final_02)
##necessary recoding
data_final$id_participant <- data_final$record_id
data_final$age <- as.numeric(NA)
data_final <- rename(data_final, cowat_k_total = cowat_k_total_calc,
cowat_p_total = cowat_p_total_calc,
cowat_s_total = cowat_s_total_calc,
cowat_n_total = cowat_n_total_calc,
dkst_cs_hs = dkefs_freesort_cstotal,
dkst_ds_hs = dkefs_freesort_descr_total)
data_final$sex <- ifelse(data_final$sex == "F", "female",ifelse(data_final$sex == "M","male", NA))
data_final$later_hand <- ifelse(data_final$later_hand == 1 | data_final$later_hand == 2, "right",
ifelse(data_final$later_hand == 3 | data_final$later_hand == 4,"left",
ifelse(data_final$later_hand == 5 | data_final$later_hand == 6,"other",NA
)))
remove(data_final_01)
remove(data_final_02)
remove(data_prefinal)
remove(data_prefinal_01)
remove(data_prefinal_01a)
remove(data_prefinal_02a)
remove(data_prefinal_02b)
##merge all data into one variable (calculated and non-calculated fields)
for (i in 1:nrow(data_final)) {
if(is.na(data_final$pasat_total[i])==T & is.na(data_final$pasat_total_calculated[i])!=T) {
data_final$pasat_total[i] <- data_final$pasat_total_calculated[i]
}
if(is.na(data_final$sdmt90_total[i])==T & is.na(data_final$sdmt90_total_calculated[i])!=T) {
data_final$sdmt90_total[i] <- data_final$sdmt90_total_calculated[i]
}
if(is.na(data_final$cvlt_total[i])==T & is.na(data_final$cvlt_total_calculated[i])!=T) {
data_final$cvlt_total[i] <- data_final$cvlt_total_calculated[i]
}
if(is.na(data_final$bvmt_total[i])==T & is.na(data_final$bvmt_total_calculated[i])!=T) {
data_final$bvmt_total[i] <- data_final$bvmt_total_calculated[i]
}
if(is.na(data_final$ravlt_total[i])==T & is.na(data_final$ravlt_total_calc[i])!=T) {
data_final$ravlt_total[i] <- data_final$ravlt_total_calc[i]
}
if(is.na(data_final$cowat_kps_total[i])==T & is.na(data_final$cowat_kps_total_calc[i])!=T) {
data_final$cowat_kps_total[i] <- data_final$cowat_kps_total_calc[i]
}
if(is.na(data_final$cowat_nkp_total[i])==T & is.na(data_final$cowat_nkp_total_calc[i])!=T) {
data_final$cowat_nkp_total[i] <- data_final$cowat_nkp_total_calc[i]
}
if(is.na(data_final$cowat_animal_total[i])==T & is.na(data_final$cowat_animal_total_calc[i])!=T) {
data_final$cowat_animal_total[i] <- data_final$cowat_animal_total_calc[i]
}
if(is.na(data_final$cowat_vege_total[i])==T & is.na(data_final$cowat_vege_total_calc[i])!=T) {
data_final$cowat_vege_total[i] <- data_final$cowat_vege_total_calc[i]
}
if(is.na(data_final$fss_total[i])==T & is.na(data_final$fss_total_calculated[i])!=T) {
data_final$fss_total[i] <- data_final$fss_total_calculated[i]
}
if(is.na(data_final$fss_total_re[i])==T & is.na(data_final$fss_total_re_calculated[i])!=T) {
data_final$fss_total_re[i] <- data_final$fss_total_re_calculated[i]
}
if(is.na(data_final$fss_total_krupp[i])==T & is.na(data_final$fss_total_krupp_calc[i])!=T) {
data_final$fss_total_krupp[i] <- data_final$fss_total_krupp_calc[i]
}
if(is.na(data_final$fss_total_v02[i])==T & is.na(data_final$fss_total_v02_calc[i])!=T) {
data_final$fss_total_v02[i] <- data_final$fss_total_v02_calc[i]
}
if(is.na(data_final$bdi_total[i])==T & is.na(data_final$bdi_total_calculated[i])!=T) {
data_final$bdi_total[i] <- data_final$bdi_total_calculated[i]
}
if(is.na(data_final$hads_depres_total[i])==T & is.na(data_final$hads_depres_total_calc[i])!=T) {
data_final$hads_depres_total[i] <- data_final$hads_depres_total_calc[i]
}
if(is.na(data_final$hads_anxiet_total[i])==T & is.na(data_final$hads_anxiet_total_calc[i])!=T) {
data_final$hads_anxiet_total[i] <- data_final$hads_anxiet_total_calc[i]
}
if(is.na(data_final$msnq_total[i])==T & is.na(data_final$msnq_total_calculated[i])!=T) {
data_final$msnq_total[i] <- data_final$msnq_total_calculated[i]
}
if(is.na(data_final$stai_x1_total[i])==T & is.na(data_final$stai_x1_total_calculated[i])!=T) {
data_final$stai_x1_total[i] <- data_final$stai_x1_total_calculated[i]
}
if(is.na(data_final$stai_x2_total[i])==T & is.na(data_final$stai_x2_total_calculated[i])!=T) {
data_final$stai_x2_total[i] <- data_final$stai_x2_total_calculated[i]
}
if(is.na(data_final$dymus_total[i])==T & is.na(data_final$dymus_total_calculated[i])!=T) {
data_final$dymus_total[i] <- data_final$dymus_total_calculated[i]
}
}
##merge FSS versions in one variable
fss_errors_01 <- filter(data_final, is.na(fss_total)==F & is.na(fss_total_re)==F)
fss_errors_02 <- filter(data_final, is.na(fss_total)==F & is.na(fss_total_v02)==F)
fss_errors_03 <- filter(data_final, is.na(fss_total)==F & is.na(fss_total_krupp)==F)
fss_errors_04 <- filter(data_final, is.na(fss_total_re)==F & is.na(fss_total_v02)==F)
fss_errors_05 <- filter(data_final, is.na(fss_total_re)==F & is.na(fss_total_krupp)==F)
fss_errors_06 <- filter(data_final, is.na(fss_total_v02)==F & is.na(fss_total_krupp)==F)
fss_error_ids <- c(fss_errors_01$record_id, fss_errors_02$record_id, fss_errors_03$record_id, fss_errors_04$record_id, fss_errors_05$record_id, fss_errors_06$record_id)
fss_merge_ready <- filter(data_final, !record_id %in% c(fss_error_ids))
vars <- c("fss_total", "fss_total_re", "fss_total_v02", "fss_total_krupp")
fss_final <- unite(fss_merge_ready, col = fss_total_merged, all_of(vars), remove = F, na.rm = T)
data_final$fss_total_merged <- as.numeric(fss_final$fss_total_merged)
data_final$fss_version <- ifelse(is.na(data_final$fss_total) != T, 1,
ifelse(is.na(data_final$fss_total_re) != T, 2,
ifelse(is.na(data_final$fss_total_v02) != T, 3,
ifelse(is.na(data_final$fss_total_krupp) != T, 4, NA
))))
remove(fss_errors_01)
remove(fss_errors_02)
remove(fss_errors_03)
remove(fss_errors_04)
remove(fss_errors_05)
remove(fss_errors_06)
remove(fss_final)
remove(fss_merge_ready)
remove(vars)
remove(fss_error_ids)
#Count cases for Leavitt
##Neuroperformance measures
###SDMT (and other BICAMS measures if available)
###Timed 25-foot walk test
###Nine-hole peg test
##PROs
###Depression
###Anxiety
###Fatigue
##All data
data_selected <- filter(data_final,
!is.na(sdmt90_total) &
!is.na(twentyfive_foot_01) &
!is.na(twentyfive_foot_02) &
!is.na(ninehp_dom_01) &
!is.na(ninehp_dom_02) &
!is.na(ninehp_nedom_01) &
!is.na(ninehp_nedom_02) &
!is.na(fss_total_merged) &
(!is.na(bdi_total) | !is.na(hads_depres_total)) &
(!is.na(stai_x1_total) | !is.na(hads_anxiet_total))
)
length(unique(data_selected$record_id))
##SCG only
data_selected_scg <- filter(data_final,
!is.na(sdmt90_total) &
!is.na(twentyfive_foot_01) &
!is.na(twentyfive_foot_02) &
!is.na(ninehp_dom_01) &
!is.na(ninehp_dom_02) &
!is.na(ninehp_nedom_01) &
!is.na(ninehp_nedom_02) &
!is.na(fss_total_merged) &
(!is.na(bdi_total) | !is.na(hads_depres_total)) &
(!is.na(stai_x1_total) | !is.na(hads_anxiet_total)) &
redcap_branch == "arm_1"
)
length(unique(data_selected_scg$record_id))