Revised tlg_template vignette

DESCRIPTION

@@ -99,4 +99,4 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 LazyDataCompression: xz
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3

R/appendix.R

@@ -86,7 +86,7 @@ postprocessing_doc <- function(doc, save_file, doc_o, type = "") {
 #' @examples
 #' example <- tempfile(fileext = ".pptx")
 #' doc <- officer::read_pptx()
-#' doc <- officer::add_slide(doc, layout = "Title and Content")
+#' doc <- officer::add_slide(doc)
 #' print(doc, target = example)
 #' doc <- initialize_doc_original(NULL, example)
 initialize_doc_original <- function(doc_original, doc_o) {

vignettes/tlg_templates.Rmd

@@ -137,12 +137,9 @@ library(assertthat)   # For assert_that() you had issues with before
 
 ```{r_function_call, include = TRUE}
 use_template(template = "t_dm_slide", function_name = "demography")
-
 ```
 This will create a file with the demography template at `./programs/R/demography.R`, whose contents are displayed below.
 ```{r, include = TRUE}
-library(dplyr)
-library(autoslider.core)
 demography <- function(adsl,
                        arm = "TRT01P",
                        vars = c("AGE", "SEX", "RACE"),
@@ -192,25 +189,15 @@ demography <- function(adsl,
 }
 
 ```
+
+
+```{r, include = FALSE}
+library(autoslider.core)
+adsl <- eg_adsl
+```
 Processing our data with the generated `t_dm_slide` script would look like：
 ```{r}
-filters::load_filters(filters, overwrite = TRUE)
-# read data
-data <- list(
-  "adsl" = eg_adsl %>%
-    mutate(
-      FASFL = SAFFL, # add FASFL for illustrative purpose for t_pop_slide
-      # DISTRTFL is needed for t_ds_slide but is missing in example data
-      DISTRTFL = sample(c("Y", "N"), size = length(TRT01A), replace = TRUE, prob = c(.1, .9))
-    ) %>%
-    preprocess_t_ds(), # this preproccessing is required by one of the autoslider.core functions
-  "adae" = eg_adae,
-  "adtte" = eg_adtte,
-  "adrs" = eg_adrs,
-  "adlb" = eg_adlb
-)
-demography(data$adsl)
-
+demography(adsl)
 ```
 Following this process, you have successfully generated a reusable `demography` function that processes clinical data, and convert it into a standard demographic table, including statistical insights like range, median, and count fractions to variables AGE, SEX, and RACE.