Closes #133 proliferate conf.level argument as appropriate across package

R/ard_effectsize_cohens_d.R

@@ -13,6 +13,8 @@
 #'   Independent tests will be run for each variable.
 #' @param id ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column name of the subject or participant ID
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... arguments passed to `effectsize::cohens_d(...)`
 #'
 #' @return ARD data frame
@@ -46,7 +48,7 @@ NULL
 
 #' @rdname ard_effectsize_cohens_d
 #' @export
-ard_effectsize_cohens_d <- function(data, by, variables, ...) {
+ard_effectsize_cohens_d <- function(data, by, variables, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -75,7 +77,7 @@ ard_effectsize_cohens_d <- function(data, by, variables, ...) {
         variable = variable,
         lst_tidy =
           cards::eval_capture_conditions(
-            effectsize::cohens_d(data[[variable]] ~ data[[by]], data = data, paired = FALSE, ...) |>
+            effectsize::cohens_d(data[[variable]] ~ data[[by]], data = data, paired = FALSE, ci = conf.level, ...) |>
               parameters::standardize_names(style = "broom")
           ),
         paired = FALSE,
@@ -89,7 +91,7 @@ ard_effectsize_cohens_d <- function(data, by, variables, ...) {
 
 #' @rdname ard_effectsize_cohens_d
 #' @export
-ard_effectsize_paired_cohens_d <- function(data, by, variables, id, ...) {
+ard_effectsize_paired_cohens_d <- function(data, by, variables, id, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -123,7 +125,7 @@ ard_effectsize_paired_cohens_d <- function(data, by, variables, id, ...) {
             # 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)
             # perform paired cohen's d test
-            effectsize::cohens_d(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ...) |>
+            effectsize::cohens_d(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ci = conf.level, ...) |>
               parameters::standardize_names(style = "broom")
           }),
         paired = TRUE,

R/ard_effectsize_hedges_g.R

@@ -13,6 +13,8 @@
 #'   tests will be run for each variable
 #' @param id ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column name of the subject or participant ID
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... arguments passed to `effectsize::hedges_g(...)`
 #'
 #' @return ARD data frame
@@ -46,7 +48,7 @@ NULL
 
 #' @rdname ard_effectsize_hedges_g
 #' @export
-ard_effectsize_hedges_g <- function(data, by, variables, ...) {
+ard_effectsize_hedges_g <- function(data, by, variables, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -79,7 +81,7 @@ ard_effectsize_hedges_g <- function(data, by, variables, ...) {
             # Will also need to remove `hedges_g` from globalVariables()
             withr::with_namespace(
               package = "effectsize",
-              code = hedges_g(data[[variable]] ~ data[[by]], paired = FALSE, ...)
+              code = hedges_g(data[[variable]] ~ data[[by]], paired = FALSE, ci = conf.level, ...)
             ) |>
               parameters::standardize_names(style = "broom")
           ),
@@ -93,7 +95,7 @@ ard_effectsize_hedges_g <- function(data, by, variables, ...) {
 
 #' @rdname ard_effectsize_hedges_g
 #' @export
-ard_effectsize_paired_hedges_g <- function(data, by, variables, id, ...) {
+ard_effectsize_paired_hedges_g <- function(data, by, variables, id, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -129,7 +131,7 @@ ard_effectsize_paired_hedges_g <- function(data, by, variables, id, ...) {
             # perform paired cohen's d test
             withr::with_namespace(
               package = "effectsize",
-              code = hedges_g(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ...)
+              code = hedges_g(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ci = conf.level, ...)
             ) |>
               parameters::standardize_names(style = "broom")
           }),

R/ard_stats_fisher_test.R

@@ -12,6 +12,8 @@
 #' @param variables ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column names to be compared. Independent tests will be computed for
 #'   each variable.
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... additional arguments passed to `fisher.test(...)`
 #'
 #' @return ARD data frame
@@ -20,7 +22,7 @@
 #' @examplesIf do.call(asNamespace("cardx")$is_pkg_installed, list(pkg = "broom", reference_pkg = "cardx"))
 #' cards::ADSL[1:30, ] |>
 #'   ard_stats_fisher_test(by = "ARM", variables = "AGEGR1")
-ard_stats_fisher_test <- function(data, by, variables, ...) {
+ard_stats_fisher_test <- function(data, by, variables, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -45,7 +47,7 @@ ard_stats_fisher_test <- function(data, by, variables, ...) {
       cards::tidy_as_ard(
         lst_tidy =
           cards::eval_capture_conditions(
-            stats::fisher.test(x = data[[variable]], y = data[[by]], ...) |>
+            stats::fisher.test(x = data[[variable]], y = data[[by]], conf.level = conf.level, ...) |>
               broom::tidy()
           ),
         tidy_result_names =

R/ard_stats_prop_test.R

@@ -10,6 +10,8 @@
 #' @param variables ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column names to be compared. Must be a binary column coded as `TRUE`/`FALSE`
 #'   or `1`/`0`. Independent tests will be computed for each variable.
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... arguments passed to `prop.test(...)`
 #'
 #' @return ARD data frame
@@ -18,7 +20,7 @@
 #' @examplesIf do.call(asNamespace("cardx")$is_pkg_installed, list(pkg = "broom", reference_pkg = "cardx"))
 #' mtcars |>
 #'   ard_stats_prop_test(by = vs, variables = am)
-ard_stats_prop_test <- function(data, by, variables, ...) {
+ard_stats_prop_test <- function(data, by, variables, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -72,6 +74,7 @@ ard_stats_prop_test <- function(data, by, variables, ...) {
             stats::prop.test(
               x = data_counts[["x"]],
               n = data_counts[["n"]],
+              conf.level = conf.level,
               ...
             ) |>
               broom::tidy() |>

R/ard_stats_t_test.R

@@ -12,6 +12,8 @@
 #'   each variable.
 #' @param id ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column name of the subject or participant ID
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... arguments passed to `t.test(...)`
 #'
 #' @return ARD data frame
@@ -43,7 +45,7 @@ NULL
 
 #' @rdname ard_stats_t_test
 #' @export
-ard_stats_t_test <- function(data, variables, by = NULL, ...) {
+ard_stats_t_test <- function(data, variables, by = NULL, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -72,7 +74,7 @@ ard_stats_t_test <- function(data, variables, by = NULL, ...) {
         lst_tidy =
           # styler: off
           cards::eval_capture_conditions(
-            if (!is_empty(by)) stats::t.test(data[[variable]] ~ data[[by]], ...) |> broom::tidy()
+            if (!is_empty(by)) stats::t.test(data[[variable]] ~ data[[by]], conf.level = conf.level, ...) |> broom::tidy()
             else stats::t.test(data[[variable]], ...) |> broom::tidy()
           ),
         # styler: on
@@ -86,7 +88,7 @@ ard_stats_t_test <- function(data, variables, by = NULL, ...) {
 
 #' @rdname ard_stats_t_test
 #' @export
-ard_stats_paired_t_test <- function(data, by, variables, id, ...) {
+ard_stats_paired_t_test <- function(data, by, variables, id, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -120,7 +122,7 @@ ard_stats_paired_t_test <- function(data, by, variables, id, ...) {
             # 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)
             # perform paired t-test
-            stats::t.test(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ...) |>
+            stats::t.test(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, conf.level = conf.level, ...) |>
               broom::tidy()
           }),
         paired = TRUE,

R/ard_stats_wilcox_test.R

@@ -12,6 +12,8 @@
 #'   each variable.
 #' @param id ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column name of the subject or participant ID.
+#' @param conf.level (scalar `numeric`)\cr
+#'   confidence level for confidence interval. Default is `0.95`.
 #' @param ... arguments passed to `wilcox.test(...)`
 #'
 #' @return ARD data frame
@@ -43,7 +45,7 @@ NULL
 
 #' @rdname ard_stats_wilcox_test
 #' @export
-ard_stats_wilcox_test <- function(data, variables, by = NULL, ...) {
+ard_stats_wilcox_test <- function(data, variables, by = NULL, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -73,7 +75,7 @@ ard_stats_wilcox_test <- function(data, variables, by = NULL, ...) {
           # styler: off
           cards::eval_capture_conditions(
             if (!is_empty(by)) {
-              stats::wilcox.test(data[[variable]] ~ data[[by]], ...) |>
+              stats::wilcox.test(data[[variable]] ~ data[[by]], conf.level = conf.level, ...) |>
                 broom::tidy()
             }
             else {
@@ -92,7 +94,7 @@ ard_stats_wilcox_test <- function(data, variables, by = NULL, ...) {
 
 #' @rdname ard_stats_wilcox_test
 #' @export
-ard_stats_paired_wilcox_test <- function(data, by, variables, id, ...) {
+ard_stats_paired_wilcox_test <- function(data, by, variables, id, conf.level = 0.95, ...) {
   set_cli_abort_call()
 
   # check installed packages ---------------------------------------------------
@@ -126,7 +128,7 @@ ard_stats_paired_wilcox_test <- function(data, by, variables, id, ...) {
             # 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)
             # perform paired wilcox test
-            stats::wilcox.test(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, ...) |>
+            stats::wilcox.test(x = data_wide[["by1"]], y = data_wide[["by2"]], paired = TRUE, conf.level = conf.level, ...) |>
               broom::tidy()
           }),
         paired = TRUE,