closes #21

.travis.yml

@@ -34,17 +34,12 @@ r_packages:
   - mvtnorm
   - rstan
   - StanHeaders
-  - LaplacesDemon
-  - logspline
   - testthat
   - remotes
   - knitr
   - rmarkdown
   - coda
-  - rstantools
-  - bridgesampling
   - BH
-  - metaBMA
 
 r_github_packages:
   - jimhester/lintr

API

@@ -5,6 +5,7 @@
 p_adjust_text(p.adjust.method)
 pairwise_caption(caption, test.description, pairwise.display = "significant", ...)
 pairwise_comparisons(data, x, y, type = "parametric", paired = FALSE, var.equal = FALSE, tr = 0.1, bf.prior = 0.707, p.adjust.method = "holm", k = 2L, ...)
+pairwise_p(data, x, y, type = "parametric", paired = FALSE, var.equal = FALSE, tr = 0.1, bf.prior = 0.707, p.adjust.method = "holm", k = 2L, ...)
 
 ## Reexported objects
 

DESCRIPTION

@@ -25,13 +25,14 @@ Depends:
     R (>= 3.6.0)
 Imports:
     broom,
+    BayesFactor,
     dplyr,
     ipmisc,
     PMCMRplus,
+    parameters,
     purrr,
     rlang,
     stats,
-    tidyBF (>= 0.2.1),
     tidyr,
     WRS2
 Suggests:

NAMESPACE

@@ -13,9 +13,11 @@ export(long_to_wide_converter)
 export(p_adjust_text)
 export(pairwise_caption)
 export(pairwise_comparisons)
+export(pairwise_p)
 export(signif_column)
 export(specify_decimal_p)
 export(tibble)
+importFrom(BayesFactor,ttestBF)
 importFrom(PMCMRplus,durbinAllPairsTest)
 importFrom(PMCMRplus,gamesHowellTest)
 importFrom(PMCMRplus,kwAllPairsDunnTest)
@@ -41,12 +43,14 @@ importFrom(ipmisc,"%<-%")
 importFrom(ipmisc,"%<>%")
 importFrom(ipmisc,"%>%")
 importFrom(ipmisc,as_tibble)
+importFrom(ipmisc,easystats_to_tidy_names)
 importFrom(ipmisc,enframe)
 importFrom(ipmisc,long_to_wide_converter)
 importFrom(ipmisc,signif_column)
 importFrom(ipmisc,specify_decimal_p)
 importFrom(ipmisc,stats_type_switch)
 importFrom(ipmisc,tibble)
+importFrom(parameters,model_parameters)
 importFrom(purrr,map2)
 importFrom(purrr,map_dfr)
 importFrom(rlang,"!!")
@@ -60,7 +64,6 @@ importFrom(stats,aov)
 importFrom(stats,na.omit)
 importFrom(stats,p.adjust)
 importFrom(stats,pairwise.t.test)
-importFrom(tidyBF,bf_ttest)
 importFrom(tidyr,gather)
 importFrom(tidyr,separate)
 importFrom(tidyr,spread)

R/global_vars.R

@@ -89,6 +89,7 @@ utils::globalVariables(
     "R",
     "adj.r.squared",
     "p.value",
+    "psihat",
     "term",
     "label",
     "loglik",

R/helpers.R

@@ -32,8 +32,11 @@ PMCMR_to_tibble <- function(mod, ...) {
   )
 }
 
-
-
+#' @name p_adjust_column_adder
+#'
+#' @importFrom stats p.adjust
+#' @importFrom dplyr mutate
+#'
 #' @noRd
 #' @keywords internal
 
@@ -42,3 +45,66 @@ p_adjust_column_adder <- function(df, p.adjust.method) {
     dplyr::mutate(p.value = stats::p.adjust(p = p.value, method = p.adjust.method)) %>%
     signif_column(data = ., p = p.value)
 }
+
+#' @importFrom BayesFactor ttestBF
+#' @importFrom dplyr mutate
+#' @importFrom parameters model_parameters
+#' @importFrom ipmisc easystats_to_tidy_names
+#'
+#' @noRd
+#' @keywords internal
+
+bf_internal_ttest <- function(data,
+                              x,
+                              y,
+                              paired = FALSE,
+                              bf.prior = 0.707,
+                              ...) {
+  # make sure both quoted and unquoted arguments are allowed
+  c(x, y) %<-% c(rlang::ensym(x), rlang::ensym(y))
+
+  # have a proper cleanup with NA removal
+  data %<>%
+    ipmisc::long_to_wide_converter(
+      data = .,
+      x = {{ x }},
+      y = {{ y }},
+      paired = paired,
+      spread = paired
+    )
+
+  # within-subjects design
+  if (isTRUE(paired)) {
+    # change names for convenience
+    colnames(data) <- c("rowid", "col1", "col2")
+
+    # extracting results from Bayesian test and creating a dataframe
+    bf_object <-
+      BayesFactor::ttestBF(
+        x = data$col1,
+        y = data$col2,
+        rscale = bf.prior,
+        paired = TRUE,
+        progress = FALSE
+      )
+  }
+
+  # between-subjects design
+  if (isFALSE(paired)) {
+    # extracting results from Bayesian test and creating a dataframe
+    bf_object <-
+      BayesFactor::ttestBF(
+        formula = rlang::new_formula({{ y }}, {{ x }}),
+        data = as.data.frame(data),
+        rscale = bf.prior,
+        paired = FALSE,
+        progress = FALSE
+      )
+  }
+
+  # extracting Bayes Factors and other details
+  parameters::model_parameters(bf_object, ...) %>%
+    ipmisc::easystats_to_tidy_names(.) %>%
+    dplyr::rename(.data = ., bf10 = bf) %>%
+    dplyr::mutate(.data = ., log_e_bf10 = log(bf10))
+}

R/pairwise_comparisons.R

@@ -1,7 +1,8 @@
 #' @title Multiple pairwise comparison tests with tidy data
 #' @name pairwise_comparisons
-#' @description Calculate parametric, non-parametric, and robust pairwise
-#'   comparisons between group levels with corrections for multiple testing.
+#' @description Calculate parametric, non-parametric, robust, and Bayes Factor
+#'   pairwise comparisons between group levels with corrections for multiple
+#'   testing.
 #'
 #' @param data A dataframe from which variables specified are to be taken. A
 #'   matrix or tables will **not** be accepted.
@@ -38,6 +39,21 @@
 #'   columns across the different types of statistics, there will be additional
 #'   columns specific to the `type` of test being run.
 #'
+#'   This function provides a unified syntax to carry out pairwise comparison
+#'   tests and internally relies on other packages to carry out these tests. For
+#'   more details about the included tests, see the documentation for the
+#'   respective functions:
+#'   \itemize{
+#'   \item *parametric* : [stats::pairwise.t.test()] (paired) and
+#'   [PMCMRplus::gamesHowellTest()] (unpaired)
+#'   \item *non-parametric* :
+#'   [PMCMRplus::durbinAllPairsTest()] (paired) and
+#'   [PMCMRplus::kwAllPairsDunnTest()] (unpaired)
+#'   \item *robust* :
+#'   [WRS2::rmmcp()] (paired) and  [WRS2::lincon()] (unpaired)
+#'   \item *Bayes Factor* : [BayesFactor::ttestBF()]
+#'   }
+#'
 #'   The `significance` column asterisks indicate significance levels of
 #'   *p*-values in the American Psychological Association (APA) mandated format:
 #'   \itemize{
@@ -57,7 +73,6 @@
 #' @importFrom purrr map2 map_dfr
 #' @importFrom broom tidy
 #' @importFrom ipmisc stats_type_switch
-#' @importFrom tidyBF bf_ttest
 #'
 #' @examples
 #'
@@ -182,8 +197,7 @@ pairwise_comparisons <- function(data,
   type <- ipmisc::stats_type_switch(type)
 
   # ensure the arguments work quoted or unquoted
-  x <- rlang::ensym(x)
-  y <- rlang::ensym(y)
+  c(x, y) %<-% c(rlang::ensym(x), rlang::ensym(y))
 
   # ---------------------------- data cleanup -------------------------------
 
@@ -241,27 +255,23 @@ pairwise_comparisons <- function(data,
 
   # ---------------------------- bayes factor --------------------------------
 
-  # print a message telling the user that this is currently not supported
   if (type == "bayes") {
-    # creating a list of dataframes with subsections of data
-    df_list <-
-      purrr::map2(
-        .x = as.character(df$group1),
-        .y = as.character(df$group2),
-        .f = function(a, b) droplevels(dplyr::filter(df_internal, {{ x }} %in% c(a, b)))
-      )
-
     # combining results into a single dataframe and returning it
     df_tidy <-
       purrr::map_dfr(
-        .x = df_list,
-        .f = ~ tidyBF::bf_ttest(
+        # creating a list of dataframes with subsections of data
+        .x = purrr::map2(
+          .x = as.character(df$group1),
+          .y = as.character(df$group2),
+          .f = function(a, b) droplevels(dplyr::filter(df_internal, {{ x }} %in% c(a, b)))
+        ),
+        # internal function to carry out BF t-test
+        .f = ~ bf_internal_ttest(
           data = .x,
           x = {{ x }},
           y = {{ y }},
           paired = paired,
-          bf.prior = bf.prior,
-          output = "results"
+          bf.prior = bf.prior
         )
       ) %>%
       dplyr::rowwise() %>%
@@ -285,8 +295,8 @@ pairwise_comparisons <- function(data,
   # ---------------------------- nonparametric ----------------------------
 
   if (type == "nonparametric") {
+    # # running Dunn test
     if (isFALSE(paired)) {
-      # # running Dunn test
       mod <-
         suppressWarnings(PMCMRplus::kwAllPairsDunnTest(
           x = y_vec,
@@ -299,9 +309,8 @@ pairwise_comparisons <- function(data,
       test.details <- "Dunn test"
     }
 
-    # converting the entered long format data to wide format
+    # # running Durbin-Conover test
     if (isTRUE(paired)) {
-      # creating model object
       mod <-
         PMCMRplus::durbinAllPairsTest(
           y = na.omit(matrix(
@@ -326,20 +335,16 @@ pairwise_comparisons <- function(data,
 
   if (type == "robust") {
     if (isFALSE(paired)) {
-      # object with all details about pairwise comparisons
-      rob_pairwise_df <-
+      wrs_obj <-
         WRS2::lincon(
           formula = rlang::new_formula({{ y }}, {{ x }}),
           data = df_internal,
           tr = tr
         )
     }
 
-    # converting to long format and then getting it back in wide so that the
-    # rowid variable can be used as the block variable
     if (isTRUE(paired)) {
-      # running pairwise multiple comparison tests
-      rob_pairwise_df <-
+      wrs_obj <-
         WRS2::rmmcp(
           y = df_internal[[rlang::as_name(y)]],
           groups = df_internal[[rlang::as_name(x)]],
@@ -350,22 +355,21 @@ pairwise_comparisons <- function(data,
 
     # extracting the robust pairwise comparisons and tidying up names
     rob_df_tidy <-
-      suppressMessages(as_tibble(rob_pairwise_df$comp, .name_repair = "unique")) %>%
+      suppressMessages(as_tibble(wrs_obj$comp, .name_repair = "unique")) %>%
       dplyr::rename(group1 = Group...1, group2 = Group...2)
 
     # cleaning the raw object and getting it in the right format
     df <-
       dplyr::full_join(
         # dataframe comparing comparison details
-        x = p_adjust_column_adder(df = rob_df_tidy, p.adjust.method = p.adjust.method) %>%
-          tidyr::gather(
-            data = .,
-            key = "key",
-            value = "rowid",
-            group1:group2
-          ),
+        x = tidyr::gather(
+          data = p_adjust_column_adder(rob_df_tidy, p.adjust.method),
+          key = "key",
+          value = "rowid",
+          group1:group2
+        ),
         # dataframe with factor levels
-        y = enframe(x = rob_pairwise_df$fnames, name = "rowid"),
+        y = enframe(x = wrs_obj$fnames, name = "rowid"),
         by = "rowid"
       ) %>%
       dplyr::select(.data = ., -rowid) %>%
@@ -375,7 +379,7 @@ pairwise_comparisons <- function(data,
     if (("p.crit") %in% names(df)) df %<>% dplyr::select(.data = ., -p.crit)
 
     # renaming confidence interval names
-    df %<>% dplyr::rename(.data = ., conf.low = ci.lower, conf.high = ci.upper)
+    df %<>% dplyr::rename(estimate = psihat, conf.low = ci.lower, conf.high = ci.upper)
 
     # test details
     test.details <- "Yuen's trimmed means test"
@@ -428,3 +432,9 @@ pairwise_comparisons <- function(data,
   # return
   return(dplyr::ungroup(df))
 }
+
+#' @name pairwise_comparisons
+#' @aliases  pairwise_comparisons
+#' @export
+
+pairwise_p <- pairwise_comparisons