removing missing values before calculating values to avoid note about…

… NA values being dropped
insightsengineering · May 6, 2024 · cea214d · cea214d
1 parent 5ffd9d6
commit cea214d
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Showing 2 changed files with 23 additions and 4 deletions.
diff --git a/R/ard_effectsize_cohens_d.R b/R/ard_effectsize_cohens_d.R
@@ -77,7 +77,13 @@ ard_effectsize_cohens_d <- function(data, by, variables, conf.level = 0.95, ...)
         variable = variable,
         lst_tidy =
           cards::eval_capture_conditions(
-            effectsize::cohens_d(data[[variable]] ~ data[[by]], data = data, paired = FALSE, ci = conf.level, ...) |>
+            effectsize::cohens_d(
+              reformulate2(by, response = variable),
+              data = data |> tidyr::drop_na(all_of(c(by, variable))),
+              paired = FALSE,
+              ci = conf.level,
+              ...
+            ) |>
               parameters::standardize_names(style = "broom") |>
               dplyr::mutate(method = "Cohen's D")
           ),
@@ -125,7 +131,10 @@ ard_effectsize_paired_cohens_d <- function(data, by, variables, id, conf.level =
         lst_tidy =
           cards::eval_capture_conditions({
             # adding this reshape inside the eval, so if there is an error it's captured in the ARD object
-            data_wide <- .paired_data_pivot_wider(data, by = by, variable = variable, id = id)
+            data_wide <-
+              data |>
+              tidyr::drop_na(all_of(c(id, by, variable))) |>
+              .paired_data_pivot_wider(by = by, variable = variable, id = id)
             # perform paired cohen's d test
             effectsize::cohens_d(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ci = conf.level, ...) |>
               parameters::standardize_names(style = "broom") |>

diff --git a/R/ard_effectsize_hedges_g.R b/R/ard_effectsize_hedges_g.R
@@ -82,7 +82,14 @@ ard_effectsize_hedges_g <- function(data, by, variables, conf.level = 0.95, ...)
             # Will also need to remove `hedges_g` from globalVariables()
             withr::with_namespace(
               package = "effectsize",
-              code = hedges_g(data[[variable]] ~ data[[by]], paired = FALSE, ci = conf.level, ...)
+              code =
+                hedges_g(
+                  reformulate2(by, response = variable),
+                  data = data |> tidyr::drop_na(all_of(c(by, variable))),
+                  paired = FALSE,
+                  ci = conf.level,
+                  ...
+                )
             ) |>
               parameters::standardize_names(style = "broom") |>
               dplyr::mutate(method = "Hedge's G")
@@ -130,7 +137,10 @@ ard_effectsize_paired_hedges_g <- function(data, by, variables, id, conf.level =
         lst_tidy =
           cards::eval_capture_conditions({
             # adding this reshape inside the eval, so if there is an error it's captured in the ARD object
-            data_wide <- .paired_data_pivot_wider(data, by = by, variable = variable, id = id)
+            data_wide <-
+              data |>
+              tidyr::drop_na(all_of(c(id, by, variable))) |>
+              .paired_data_pivot_wider(by = by, variable = variable, id = id)
             # perform paired cohen's d test
             withr::with_namespace(
               package = "effectsize",