I want to iteratively process a master list of comparisons using
group_walk() as an alternative method to import batches of .csv files.
I have the code for iteratively importing batch csvs here:
#Import list of csv files from directory, formatted as:
|rownm | neg | pos |
|------|-----|-----|
|neg |19 |18 |
|pos |5 |141 |
```
library(tidyverse) # for cleaning and shaping data
library(epiR)
library(irrCAC)
all_epi_files <- list.files("congtables", pattern = "*.csv",
full.names = TRUE)
#Make export directory
check_create_dir <- function(the_dir) {
if (!dir.exists(the_dir)) {
dir.create(the_dir, recursive = TRUE) } #Creates a directory if it
doesn't already exist
}
the_dir_ex <- "data_generated/epidata" #Name the new desired directory
check_create_dir(the_dir_ex) #Make the directory if it doesn't already exist
#Make function for the series of analyses
epi_analysis <- function(a_csv, the_dir){
#Import data as inserted variables
dat2 <- read_csv(a_csv)%>%
remove_rownames %>%
column_to_rownames(var="rownm") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(a_csv)),
na = "999.99",
row.names = FALSE)
}
#Execute functions
lapply(all_epi_files,
FUN = epi_analysis,
the_dir = the_dir_ex)
```
But instead I would like to input a dataset that looks like this:
|Test Assay | Var1 | Var2 |Freq|
|-----------|------|------|----|
|Assay1 |neg |neg |19 |
|Assay1 |neg |pos |5 |
|Assay1 |pos |neg |8 |
|Assay1 |pos |pos |141 |
|Assay2 |neg |neg |25 |
|Assay2 |neg |pos |6 |
|Assay2 |pos |neg |17 |
|Assay2 |pos |pos |33 |
|Assay3 |neg |neg |99 |
|Assay3 |neg |pos |20 |
|Assay3 |pos |neg |5 |
|Assay3 |pos |pos |105 |
I want to use the same function epi_analysis and export a csv for each
Test Assay (in this example Assay1, Assay2, and Assay3). So far I
have:
```
#Make export directory
check_create_dir <- function(the_dir) {
if (!dir.exists(the_dir)) {
dir.create(the_dir, recursive = TRUE) } #Creates a directory if it
doesn't already exist
}
the_dir_ex <- "data_generated/epidata" #Name the new desired directory
check_create_dir(the_dir_ex) #Make the directory if it doesn't already exist
#Make function for the series of analyses
epi_analysis <- function(.x, the_dir){
#Clean data
dat2 <- .x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(.x$TestAssay)),
na = "999.99",
row.names = FALSE)
}
data <- read_csv("data_raw/EpiTest.csv") %>%
group_by(TestAssay)%>%
group_map(~ epi_analysis)
```
But the only output I see is:
```
[[1]]
function(.x, the_dir){
#Clean data
dat2 <- .x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(.x$TestAssay)),
na = "999.99",
row.names = FALSE)
}
[[2]]
function(.x, the_dir){
#Clean data
dat2 <- .x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(.x$TestAssay)),
na = "999.99",
row.names = FALSE)
}
[[3]]
function(.x, the_dir){
#Clean data
dat2 <- .x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(.x$TestAssay)),
na = "999.99",
row.names = FALSE)
}
[[4]]
function(.x, the_dir){
#Clean data
dat2 <- .x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa<-epi.kappa(dat2)
gwet <- gwet.ac1.table(dat2)
kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
ests <- c(round(rval$elements$sensitivity$est, digits = 3),
round(rval$elements$specificity$est, digits = 3),
round(rval$element$pfp$est, digits = 3),
round(rval$element$pfn$est, digits = 3),
round(kappa2$coeff.val, digits = 3),
round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
paste(round(rval$elements$specificity$lower, digits = 3),
round(rval$elements$specificity$upper, digits = 3), sep = ","),
paste(round(rval$element$pfp$lower, digits = 3),
round(rval$element$pfp$upper, digits = 3), sep = ","),
paste(round(rval$element$pfn$lower, digits = 3),
round(rval$element$pfn$upper, digits = 3), sep = ","),
kappa2$coeff.ci,
gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
write.csv(df,
file = paste0(the_dir, "/", basename(.x$TestAssay)),
na = "999.99",
row.names = FALSE)
}
```
and there are no csvs in my epidata folder. Any
suggestions/corrections welcomed. I haven't used group_map() before,
but I am keen to use it.
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