IndrajeetPatil · IndrajeetPatil · Mar 22, 2024 · Mar 22, 2024 · Mar 22, 2024 · Mar 22, 2024
diff --git a/API b/API
@@ -6,6 +6,7 @@ add_expression_col(data, paired = FALSE, statistic.text = NULL, effsize.text = N
 centrality_description(data, x, y, type = "parametric", conf.level = NULL, tr = 0.2, digits = 2L, ...)
 contingency_table(data, x, y = NULL, paired = FALSE, type = "parametric", counts = NULL, ratio = NULL, alternative = "two.sided", digits = 2L, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, ...)
 corr_test(data, x, y, type = "parametric", digits = 2L, conf.level = 0.95, tr = 0.2, bf.prior = 0.707, ...)
+extract_stats_type(type)
 long_to_wide_converter(data, x, y, subject.id = NULL, paired = TRUE, spread = TRUE, ...)
 meta_analysis(data, type = "parametric", random = "mixture", digits = 2L, conf.level = 0.95, ...)
 one_sample_test(data, x, type = "parametric", test.value = 0, alternative = "two.sided", digits = 2L, conf.level = 0.95, tr = 0.2, bf.prior = 0.707, effsize.type = "g", ...)

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: statsExpressions
 Title: Tidy Dataframes and Expressions with Statistical Details
-Version: 1.5.4
+Version: 1.5.4.9000
 Authors@R: 
     person(given = "Indrajeet",
            family = "Patil",

diff --git a/NAMESPACE b/NAMESPACE
@@ -9,6 +9,7 @@ export(as_tibble)
 export(centrality_description)
 export(contingency_table)
 export(corr_test)
+export(extract_stats_type)
 export(long_to_wide_converter)
 export(meta_analysis)
 export(one_sample_test)

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,5 @@
+# statsExpressions 1.5.4.9000
+
 # statsExpressions 1.5.4
 
 ## MAJOR CHANGES

diff --git a/R/add-expression-col.R b/R/add-expression-col.R
@@ -101,8 +101,8 @@ add_expression_col <- function(
   df_expr <- data %>% # convert needed columns to character type
     .data_to_char(digits, digits.df, digits.df.error) %>%
     mutate(
-      statistic.text     = statistic.text %||% stat_text_switch(tolower(method)),
-      es.text            = effsize.text %||% estimate_type_switch(tolower(effectsize)),
+      statistic.text     = statistic.text %||% extract_statistic_text(tolower(method)),
+      es.text            = effsize.text %||% extract_estimate_type(tolower(effectsize)),
       prior.distribution = prior_switch(tolower(method)),
       n.obs              = .prettyNum(n.obs)
     )

diff --git a/R/centrality-description.R b/R/centrality-description.R
@@ -40,7 +40,7 @@ centrality_description <- function(
 
   # styler: off
   centrality <- case_match(
-    stats_type_switch(type),
+    extract_stats_type(type),
     "parametric"    ~ "mean",
     "nonparametric" ~ "median",
     "robust"        ~ "trimmed",

diff --git a/R/contingency-table.R b/R/contingency-table.R
@@ -66,7 +66,7 @@ contingency_table <- function(
     ...) {
   # data -------------------------------------------
 
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
   test <- ifelse(quo_is_null(enquo(y)), "1way", "2way")
 
   data %<>%

diff --git a/R/corr-test.R b/R/corr-test.R
@@ -37,7 +37,7 @@ corr_test <- function(
     tr = 0.2,
     bf.prior = 0.707,
     ...) {
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
 
   stats_df <- correlation::correlation(
     data           = select(ungroup(data), {{ x }}, {{ y }}) %>% tidyr::drop_na(),

diff --git a/R/meta-analysis.R b/R/meta-analysis.R
@@ -63,7 +63,7 @@
 #'
 #' # ----------------------- Bayesian ----------------------------------
 #'
-#' suppressWarnings(meta_analysis(dat, type = "bayes"))
+#' meta_analysis(dat, type = "bayes")
 #'
 #' @export
 meta_analysis <- function(
@@ -73,7 +73,7 @@ meta_analysis <- function(
     digits = 2L,
     conf.level = 0.95,
     ...) {
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
 
   # nolint start: line_length_linter.
   c(.ns, .fn, .f.args) %<-% switch(type,
@@ -85,7 +85,6 @@ meta_analysis <- function(
 
   check_if_installed(.ns)
 
-  # construct a call and then extract a tidy data frame
   stats_df <- eval(call2(.fn = .fn, .ns = .ns, data = data, !!!.f.args)) %>%
     tidy_model_parameters(include_studies = FALSE, ci = conf.level)
 

diff --git a/R/one-sample-test.R b/R/one-sample-test.R
@@ -7,7 +7,7 @@
 #' @param effsize.type Type of effect size needed for *parametric* tests. The
 #'   argument can be `"d"` (for Cohen's *d*) or `"g"` (for Hedge's *g*).
 #' @inheritParams long_to_wide_converter
-#' @inheritParams stats_type_switch
+#' @inheritParams extract_stats_type
 #' @inheritParams add_expression_col
 #' @inheritParams two_sample_test
 #' @inheritParams oneway_anova
@@ -46,7 +46,7 @@ one_sample_test <- function(
     bf.prior = 0.707,
     effsize.type = "g",
     ...) {
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
   x_vec <- stats::na.omit(pull(data, {{ x }}))
 
   # parametric ---------------------------------------

diff --git a/R/oneway-anova.R b/R/oneway-anova.R
@@ -18,7 +18,7 @@
 #' ```
 #'
 #' @inheritParams long_to_wide_converter
-#' @inheritParams stats_type_switch
+#' @inheritParams extract_stats_type
 #' @param conf.level Scalar between `0` and `1` (default: `95%`
 #' confidence/credible intervals, `0.95`). If `NULL`, no confidence intervals
 #' will be computed.
@@ -145,7 +145,7 @@ oneway_anova <- function(
     ...) {
   # data -------------------------------------------
 
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
   c(x, y) %<-% c(ensym(x), ensym(y))
 
   data %<>% long_to_wide_converter(

diff --git a/R/pairwise-comparisons.R b/R/pairwise-comparisons.R
@@ -7,7 +7,7 @@
 #' comparisons between group levels with corrections for multiple testing.
 #'
 #' @inheritParams long_to_wide_converter
-#' @inheritParams stats_type_switch
+#' @inheritParams extract_stats_type
 #' @inheritParams oneway_anova
 #' @param p.adjust.method Adjustment method for *p*-values for multiple
 #'   comparisons. Possible methods are: `"holm"` (default), `"hochberg"`,
@@ -153,7 +153,7 @@ pairwise_comparisons <- function(
     ...) {
   # data -------------------------------------------
 
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
   c(x, y) %<-% c(ensym(x), ensym(y))
 
   data %<>% long_to_wide_converter(

diff --git a/R/switch-functions.R b/R/switch-functions.R
@@ -1,4 +1,4 @@
-#' @name stats_type_switch
+#' @name extract_stats_type
 #' @title Switch the type of statistics.
 #'
 #' @description
@@ -19,22 +19,25 @@
 #' @autoglobal
 #'
 #' @examples
-#' stats_type_switch("p")
-#' stats_type_switch("bf")
+#' extract_stats_type("p")
+#' extract_stats_type("bf")
 #' @export
 # styler: off
-stats_type_switch <- function(type) {
+extract_stats_type <- function(type) {
   case_when(
-    grepl("^n|^s", type) ~ "nonparametric", # s is for Spearman's rho
-    grepl("^r", type)    ~ "robust",
-    grepl("^b", type)    ~ "bayes",
-    TRUE                 ~ "parametric"
+    grepl("^n", type) ~ "nonparametric",
+    grepl("^r", type) ~ "robust",
+    grepl("^b", type) ~ "bayes",
+    TRUE              ~ "parametric"
   )
 }
 
+#' @rdname extract_stats_type
+#' @export
+stats_type_switch <- extract_stats_type
 
 #' @noRd
-estimate_type_switch <- function(x) {
+extract_estimate_type <- function(x) {
   case_when(
     .grepl("pearson's c", x)      ~ list(quote(widehat(italic("C"))["Pearson"])),
     .grepl("cohen's d", x)        ~ list(quote(widehat(italic("d"))["Cohen"])),
@@ -62,7 +65,7 @@ estimate_type_switch <- function(x) {
 }
 
 #' @noRd
-stat_text_switch <- function(x) {
+extract_statistic_text <- function(x) {
   case_when(
     grepl("^welch", x)               ~ list(quote(italic("t")["Welch"])),
     grepl("afex| of means$", x)      ~ list(quote(italic("F")["Fisher"])),
@@ -93,7 +96,7 @@ prior_switch <- function(x) {
   )
 }
 
-#' @note Don't curry using `purrr::partial()` because it causes `Found a .Internal call` warning.
+#' @note Don't curry using `purrr::partial()` because it causes `"Found a .Internal call"` warning.
 #' @noRd
 .grepl <- function(pattern, x) grepl(pattern, x, fixed = TRUE)
 

diff --git a/R/two-sample-test.R b/R/two-sample-test.R
@@ -5,7 +5,7 @@
 #' Parametric, non-parametric, robust, and Bayesian two-sample tests.
 #'
 #' @inheritParams long_to_wide_converter
-#' @inheritParams stats_type_switch
+#' @inheritParams extract_stats_type
 #' @inheritParams one_sample_test
 #' @inheritParams oneway_anova
 #' @inheritParams stats::t.test
@@ -49,7 +49,7 @@ two_sample_test <- function(
     ...) {
   # data -------------------------------------------
 
-  type <- stats_type_switch(type)
+  type <- extract_stats_type(type)
   c(x, y) %<-% c(ensym(x), ensym(y))
 
   data %<>% long_to_wide_converter(

diff --git a/man/stats_type_switch.Rd → man/extract_stats_type.Rd b/man/stats_type_switch.Rd → man/extract_stats_type.Rd
diff --git a/man/meta_analysis.Rd b/man/meta_analysis.Rd
diff --git a/tests/testthat/test-meta-random-bayes.R b/tests/testthat/test-meta-random-bayes.R
@@ -4,13 +4,13 @@ test_that(
     skip_if_not_installed("metaBMA")
 
     set.seed(123)
-    df <- suppressWarnings(meta_analysis(
+    df <- meta_analysis(
       type = "bayes",
       data = data_meta,
       digits = 3L,
       iter = 1000L,
       summarize = "integrate"
-    ))
+    )
 
     expect_type(df, "list")
 

diff --git a/tests/testthat/test-stats-type-switch.R b/tests/testthat/test-stats-type-switch.R
@@ -1,12 +1,12 @@
 test_that(
   desc = "switch for stats type works",
   code = {
-    expect_identical(stats_type_switch("p"), "parametric")
-    expect_identical(stats_type_switch("pearson"), "parametric")
-    expect_identical(stats_type_switch("non-parametric"), "nonparametric")
-    expect_identical(stats_type_switch("np"), "nonparametric")
-    expect_identical(stats_type_switch("r"), "robust")
-    expect_identical(stats_type_switch("bf"), "bayes")
-    expect_identical(stats_type_switch("xxx"), "parametric")
+    expect_identical(extract_stats_type("p"), "parametric")
+    expect_identical(extract_stats_type("pearson"), "parametric")
+    expect_identical(extract_stats_type("non-parametric"), "nonparametric")
+    expect_identical(extract_stats_type("np"), "nonparametric")
+    expect_identical(extract_stats_type("r"), "robust")
+    expect_identical(extract_stats_type("bf"), "bayes")
+    expect_identical(extract_stats_type("xxx"), "parametric")
   }
 )