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pharmaverse · Sep 23, 2024 · 796cc3f · 796cc3f
1 parent 31aadcd
commit 796cc3f
Showing 1 changed file with 11 additions and 10 deletions.
diff --git a/R/derive_blfl.R b/R/derive_blfl.R
@@ -354,9 +354,9 @@ derive_blfl <- function(sdtm_in,
 
   # Filter out rows where --ORRES is missing. Filter out --ORRES in
   # ("ND", "NOT DONE") as well.
-  bad_orres_rows <- is.na(ds_mod[[domain_prefixed_names["orres"]]]) |
-    trimws(ds_mod[[domain_prefixed_names["orres"]]]) %in% c("ND", "NOT DONE", "")
-  ds_mod <- ds_mod[!bad_orres_rows, ]
+  ds_mod <- ds_mod |>
+  dplyr::filter(!(is.na(.data[[domain_prefixed_names["orres"]]]) |
+    trimws(.data[[domain_prefixed_names["orres"]]]) %in% c("ND", "NOT DONE", "")))
 
   # Filter out rows where --STAT is not equal to "NOT DONE"
   ds_mod <-
@@ -374,10 +374,10 @@ derive_blfl <- function(sdtm_in,
   }
 
   # Checking for columns of interest
-  con_col <- c(domain_prefixed_names[c("testcd", "dtc", "var_tpt")], "VISIT")
+  con_col <- c(domain_prefixed_names[c("testcd", "dtc", "tpt")], "VISIT")
 
-  # Drop those columns from the list which are not present in ds_in
-  con_col <- con_col[con_col %in% names(sdtm_in)]
+  # Drop those columns from the list which are not present in ds_mod
+  con_col <- con_col[con_col %in% names(ds_mod)]
 
   # Check for any column which is all NA and removing it from con_col list
   h <- which(sapply(ds_mod, function(x) all(is.na(x))))
@@ -438,16 +438,17 @@ derive_blfl <- function(sdtm_in,
     dplyr::filter(
       dom_dt == ref_dt,
       is.na(dom_tm) | is.na(ref_tm) | dom_tm == ref_tm,
-      (VISIT %in% baseline_visits & get(domain_prefixed_names["tpt"]) %in% baseline_timepoints) |
+      (VISIT %in% baseline_visits & !!rlang::sym(domain_prefixed_names["tpt"]) %in% baseline_timepoints) |
         (VISIT %in% baseline_visits & length(baseline_timepoints) == 0L) |
-        (get(domain_prefixed_names["tpt"]) %in% baseline_timepoints & length(baseline_visits) == 0L)
+        (!!rlang::sym(domain_prefixed_names["tpt"]) %in% baseline_timepoints & length(baseline_visits) == 0L)
     )
 
   # Combine (*A) and (*B) and (*C)
-  ds_base <- rbind(ds_subset_lt, ds_subset_eq_1, ds_subset_eq_2)
+  ds_base <- dplyr::bind_rows(ds_subset_lt, ds_subset_eq_1, ds_subset_eq_2)
 
   # Sort the rows in ascending order with respect to columns from con_col
-  ds_base <- dplyr::arrange_at(ds_base, c("USUBJID", con_col))
+  ds_base <- ds_base |>
+    dplyr::arrange(USUBJID, !!!rlang::syms(con_col))
 
   if (nrow(ds_base) == 0L) {
     cli::cli_inform("There are no baseline records.")