Closes #133 proliferate conf.level argument as appropriate across p…

…ackage (#142)

**What changes are proposed in this pull request?**
Adds `conf.level` argument to variety of functions for consistency

Provide more detail here as needed.

Closes #133


--------------------------------------------------------------------------------

Pre-review Checklist (if item does not apply, mark is as complete)
- [x] **All** GitHub Action workflows pass with a ✅
- [x] PR branch has pulled the most recent updates from master branch:
`usethis::pr_merge_main()`
- [x] If a bug was fixed, a unit test was added.
- [x] If a new `ard_*()` function was added, it passes the ARD
structural checks from `cards::check_ard_structure()`.
- [x] If a new `ard_*()` function was added, `set_cli_abort_call()` has
been set.
- [x] If a new `ard_*()` function was added and it depends on another
package (such as, `broom`), `is_pkg_installed("broom", reference_pkg =
"cardx")` has been set in the function call and the following added to
the roxygen comments: `@examplesIf
do.call(asNamespace("cardx")$is_pkg_installed, list(pkg = "broom"",
reference_pkg = "cardx"))`
- [x] Code coverage is suitable for any new functions/features
(generally, 100% coverage for new code): `devtools::test_coverage()`

Reviewer Checklist (if item does not apply, mark is as complete)

- [x] If a bug was fixed, a unit test was added.
- [x] Code coverage is suitable for any new functions/features:
`devtools::test_coverage()`

When the branch is ready to be merged:
- [x] Update `NEWS.md` with the changes from this pull request under the
heading "`# cardx (development version)`". If there is an issue
associated with the pull request, reference it in parentheses at the end
update (see `NEWS.md` for examples).
- [ ] **All** GitHub Action workflows pass with a ✅
- [ ] Approve Pull Request
- [ ] Merge the PR. Please use "Squash and merge" or "Rebase and merge".

---------

Co-authored-by: Daniel Sjoberg <[email protected]>

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 ---------------------------------------------------
@@ -60,7 +62,7 @@ ard_effectsize_cohens_d <- function(data, by, variables, ...) {
   data <- dplyr::ungroup(data)
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
   check_scalar(by)
-
+  check_range(conf.level, range = c(0, 1))
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
     return(dplyr::tibble())
@@ -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 ---------------------------------------------------
@@ -105,6 +107,7 @@ ard_effectsize_paired_cohens_d <- function(data, by, variables, id, ...) {
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }}, id = {{ id }})
   check_scalar(by)
   check_scalar(id)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -123,7 +126,7 @@ 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 ---------------------------------------------------
@@ -59,6 +61,7 @@ ard_effectsize_hedges_g <- function(data, by, variables, ...) {
   data <- dplyr::ungroup(data)
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
   check_scalar(by)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -79,7 +82,7 @@ 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 +96,7 @@ 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 ---------------------------------------------------
@@ -109,6 +112,7 @@ ard_effectsize_paired_hedges_g <- function(data, by, variables, id, ...) {
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }}, id = {{ id }})
   check_scalar(by)
   check_scalar(id)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -129,7 +133,7 @@ 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 ---------------------------------------------------
@@ -33,6 +35,7 @@ ard_stats_fisher_test <- function(data, by, variables, ...) {
   check_data_frame(data)
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
   check_scalar(by)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -45,7 +48,7 @@ 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 ---------------------------------------------------
@@ -29,6 +31,7 @@ ard_stats_prop_test <- function(data, by, variables, ...) {
   check_not_missing(variables)
   check_not_missing(by)
   check_data_frame(data)
+  check_range(conf.level, range = c(0, 1))
 
   # process inputs -------------------------------------------------------------
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
@@ -72,6 +75,7 @@ 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 ---------------------------------------------------
@@ -56,6 +58,7 @@ ard_stats_t_test <- function(data, variables, by = NULL, ...) {
   data <- dplyr::ungroup(data)
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
   check_scalar(by, allow_empty = TRUE)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -72,7 +75,7 @@ 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 +89,7 @@ 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 +123,7 @@ 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 ---------------------------------------------------
@@ -56,6 +58,7 @@ ard_stats_wilcox_test <- function(data, variables, by = NULL, ...) {
   data <- dplyr::ungroup(data)
   cards::process_selectors(data, by = {{ by }}, variables = {{ variables }})
   check_scalar(by, allow_empty = TRUE)
+  check_range(conf.level, range = c(0, 1))
 
   # if no variables selected, return empty tibble ------------------------------
   if (is_empty(variables)) {
@@ -73,7 +76,7 @@ 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 +95,7 @@ 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 +129,7 @@ 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,

R/ard_survey_svychisq.R

@@ -5,7 +5,7 @@
 #' Only two-way comparisons are supported.
 #'
 #' @param data (`survey.design`)\cr
-#'   a survey design object often created with the {survey} package
+#'   a survey design object often created with the \{survey\} package
 #' @param by ([`tidy-select`][dplyr::dplyr_tidy_select])\cr
 #'   column name to compare by.
 #' @param variables ([`tidy-select`][dplyr::dplyr_tidy_select])\cr