made the prior type more explicit

IndrajeetPatil · Feb 11, 2021 · 5f01107 · 5f01107 · lintr-bot · Feb 11, 2021
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diff --git a/.gitignore b/.gitignore
@@ -1,6 +1,50 @@
+Meta
+doc
+# Windows image file caches
+Thumbs.db
+ehthumbs.db
+
+# Folder config file
+Desktop.ini
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+# Windows Installer files
+*.cab
+*.msi
+*.msm
+*.msp
+# Windows shortcuts
+*.lnk
+# =========================
+# Operating System Files
+# OSX
+.DS_Store
+.AppleDouble
+.LSOverride
+# Thumbnails
+._*
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk
+# R Studio files
 .Rproj.user
 .Rhistory
 .RData
+.Ruserdata
 inst/doc
-doc
-Meta
+.httr-oauth
+revdep/checks
+revdep/library
+revdep/checks.noindex
+revdep/library.noindex
+revdep/data.sqlite
diff --git a/API b/API
@@ -9,7 +9,7 @@ expr_meta_random(data, type = "parametric", random = "mixture", k = 2L, conf.lev
 expr_oneway_anova(data, x, y, subject.id = NULL, type = "parametric", paired = FALSE, k = 2L, conf.level = 0.95, effsize.type = "omega", var.equal = FALSE, bf.prior = 0.707, tr = 0.2, nboot = 100, top.text = NULL, output = "expression", ...)
 expr_t_onesample(data, x, type = "parametric", test.value = 0, k = 2L, conf.level = 0.95, tr = 0.2, bf.prior = 0.707, effsize.type = "g", nboot = 100L, top.text = NULL, output = "expression", ...)
 expr_t_twosample(data, x, y, subject.id = NULL, type = "parametric", paired = FALSE, k = 2L, conf.level = 0.95, effsize.type = "g", var.equal = FALSE, bf.prior = 0.707, tr = 0.2, nboot = 100, top.text = NULL, output = "expression", ...)
-expr_template(data, no.parameters = 0L, bayesian = FALSE, statistic.text = NULL, effsize.text = NULL, top.text = NULL, prior.text = NULL, n = NULL, n.text = NULL, paired = FALSE, centrality = "median", conf.method = "HDI", k = 2L, k.df = 0L, k.df.error = 0L, ...)
+expr_template(data, no.parameters = 0L, bayesian = FALSE, statistic.text = NULL, effsize.text = NULL, top.text = NULL, prior.distribution = NULL, prior.type = NULL, n = NULL, n.text = NULL, paired = FALSE, conf.method = "HDI", k = 2L, k.df = 0L, k.df.error = 0L, ...)
 tidy_model_effectsize(data)
 tidy_model_parameters(model, ...)
 

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -27,7 +27,7 @@ Depends:
 Imports:
     afex,
     BayesFactor,
-    correlation (>= 0.5.0.1),
+    correlation (>= 0.5.1),
     dplyr,
     effectsize (>= 0.4.3),
     insight (>= 0.12.0.1),

diff --git a/R/helpers_expr_templates.R b/R/helpers_expr_templates.R
@@ -9,6 +9,9 @@
 #' Ideally, this dataframe would come from having run `tidy_model_parameters`
 #' function on your model object.
 #'
+#' This function is currently **not** stable and should not be used outside of
+#' this package context.
+#'
 #' @param no.parameters An integer that specifies that the number of parameters
 #'   for the statistical test. Can be `0` for non-parametric tests, `1` for
 #'   tests based on *t*-statistic or chi-squared statistic, `2` for tests based
@@ -44,13 +47,11 @@
 #'   what the `n` stands for. If `NULL`, defaults to
 #'   `quote(italic("n")["pairs"])` if `paired = TRUE`, and to
 #'   `quote(italic("n")["obs"])` if `paired = FALSE`.
-#' @param prior.text A character that specifies the prior type.
+#' @param prior.distribution A character that specifies the prior type.
 #' @param effsize.text A character that specifies the relevant effect size.
 #' @param bayesian Is this Bayesian analysis? Defaults to `FALSE`. The template
 #'   is slightly different for Bayesian analysis.
-#' @param centrality The point-estimates (centrality indices) to compute.
-#'   Character (vector) or list with one or more of these options: `"median"`,
-#'   `"mean"`, `"MAP"` or `"all"`.
+#' @param prior.type The type of prior.
 #' @param conf.method The type of index used for Credible Interval. Can be
 #'   `"hdi"` (default), `"eti"`, or `"si"` (see `si()`, `hdi()`, `eti()`
 #'   functions from `bayestestR` package).
@@ -96,11 +97,11 @@ expr_template <- function(data,
                           statistic.text = NULL,
                           effsize.text = NULL,
                           top.text = NULL,
-                          prior.text = NULL,
+                          prior.distribution = NULL,
+                          prior.type = NULL,
                           n = NULL,
                           n.text = NULL,
                           paired = FALSE,
-                          centrality = "median",
                           conf.method = "HDI",
                           k = 2L,
                           k.df = 0L,
@@ -130,35 +131,37 @@ expr_template <- function(data,
   if (isFALSE(paired) && is.null(n.text)) n.text <- quote(italic("n")["obs"])
   if (is.null(statistic.text)) statistic.text <- stat_text_switch(data$method[[1]])
   if (is.null(effsize.text)) effsize.text <- estimate_type_switch(data$effectsize[[1]])
-  if (is.null(prior.text) && bayesian) prior.text <- prior_type_switch(data$method[[1]])
   if ("conf.level" %in% names(data)) conf.level <- data$conf.level[[1]] else conf.level <- 0.95
 
   # -------------------------- Bayesian analysis ------------------------------
 
   if (isTRUE(bayesian)) {
+    if (is.null(prior.distribution)) prior.distribution <- prior_switch(data$method[[1]])
+    if (is.null(prior.type)) prior.type <- prior_type_switch(data$method[[1]])
+
     # Bayesian expression
     expression <-
       substitute(
         atop(
           displaystyle(top.text),
           expr = paste(
             "log"["e"] * "(BF"["01"] * ") = " * bf * ", ",
-            widehat(effsize.text)[centrality]^"posterior" * " = " * estimate * ", ",
+            widehat(effsize.text)[prior.type]^"posterior" * " = " * estimate * ", ",
             "CI"[conf.level]^conf.method * " [" * estimate.LB * ", " * estimate.UB * "], ",
-            prior.text * " = " * bf.prior
+            prior.distribution * " = " * bf.prior
           )
         ),
         env = list(
           top.text = top.text,
           effsize.text = effsize.text,
-          centrality = centrality,
+          prior.type = prior.type,
           conf.level = paste0(conf.level * 100, "%"),
           conf.method = toupper(conf.method),
           bf = format_num(-log(data$bf10[[1]]), k),
           estimate = format_num(estimate, k),
           estimate.LB = format_num(estimate.LB, k),
           estimate.UB = format_num(estimate.UB, k),
-          prior.text = prior.text,
+          prior.distribution = prior.distribution,
           bf.prior = format_num(data$prior.scale[[1]], k)
         )
       )
@@ -379,13 +382,26 @@ estimate_type_switch <- function(x) {
 
 #' @noRd
 
-prior_type_switch <- function(x) {
+prior_switch <- function(x) {
   dplyr::case_when(
     grepl("contingency", tolower(x)) ~ quote(italic("a")["Gunel-Dickey"]),
+    grepl("correlation", tolower(x)) ~ quote(italic("r")["beta"]^"JZS"),
     TRUE ~ quote(italic("r")["Cauchy"]^"JZS")
   )
 }
 
 #' @noRd
 
+prior_type_switch <- function(x) {
+  dplyr::case_when(
+    grepl("contingency", tolower(x)) ~ list("Cramer"),
+    grepl("correlation", tolower(x)) ~ list("Pearson"),
+    grepl("t-|meta-", tolower(x)) ~ list("difference"),
+    grepl("linear", tolower(x)) ~ list("Bayesian"),
+    TRUE ~ list(NULL)
+  )[[1]]
+}
+
+#' @noRd
+
 .prettyNum <- function(x) prettyNum(x, big.mark = ",", scientific = FALSE)
diff --git a/R/meta_random.R b/R/meta_random.R
@@ -116,7 +116,6 @@ expr_meta_random <- function(data,
       no.parameters = 0L,
       k = k,
       top.text = top.text,
-      centrality = "mean",
       bayesian = ifelse(type == "bayes", TRUE, FALSE)
     )
 

diff --git a/R/oneway_anova.R b/R/oneway_anova.R
@@ -32,6 +32,15 @@
 #' @param ... Additional arguments (currently ignored).
 #' @inheritParams stats::oneway.test
 #'
+#' @note
+#' 1. Please note that the function expects that the data is
+#'   already sorted by subject/repeated measures ID.
+#'
+#' 2. To carry out Bayesian analysis for ANOVA designs, you will need to install
+#' the development version of `BayesFactor` (`0.9.12-4.3`). You can download it
+#' by running:
+#' `remotes::install_github("richarddmorey/BayesFactor/pkg/BayesFactor")`.
+#'
 #' @importFrom dplyr select rename matches
 #' @importFrom rlang !! !!! quo_is_null eval_tidy expr enexpr ensym exec new_formula
 #' @importFrom stats oneway.test
@@ -206,11 +215,7 @@ expr_oneway_anova <- function(data,
     # tidying it up
     stats_df <- tidy_model_parameters(mod)
     effsize_df <-
-      suppressWarnings(rlang::exec(
-        .fn = .f.es,
-        model = mod,
-        ci = conf.level
-      )) %>%
+      suppressWarnings(rlang::exec(.fn = .f.es, model = mod, ci = conf.level)) %>%
       tidy_model_effectsize(.)
 
     # combining dataframes

diff --git a/README.Rmd b/README.Rmd
@@ -5,8 +5,13 @@ output: github_document
   <!-- README.md is generated from README.Rmd. Please edit that file -->
 
 ```{r, echo = FALSE}
-# show me all columns
-options(tibble.width = Inf, pillar.bold = TRUE, pillar.subtle_num = TRUE)
+options(
+  tibble.width = Inf,
+  pillar.bold = TRUE,
+  pillar.neg = TRUE,
+  pillar.subtle_num = TRUE,
+  pillar.min_chars = Inf
+)
 
 knitr::opts_chunk$set(
   collapse = TRUE,

diff --git a/codemeta.json b/codemeta.json
@@ -22,7 +22,7 @@
     "name": "R",
     "url": "https://r-project.org"
   },
-  "runtimePlatform": "R Under development (unstable) (2021-01-13 r79826)",
+  "runtimePlatform": "R version 4.0.3 (2020-10-10)",
   "author": [
     {
       "@type": "Person",
@@ -202,7 +202,7 @@
       "@type": "SoftwareApplication",
       "identifier": "correlation",
       "name": "correlation",
-      "version": ">= 0.5.0.1",
+      "version": ">= 0.5.1",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -392,6 +392,5 @@
     "name": "Comprehensive R Archive Network (CRAN)",
     "url": "https://cran.r-project.org"
   },
-  "fileSize": "3910.285KB",
-  "readme": "https://github.com/IndrajeetPatil/statsExpressions/blob/master/README.md"
+  "fileSize": "3833.346KB"
 }
diff --git a/inst/WORDLIST b/inst/WORDLIST
@@ -35,9 +35,9 @@ bayesian
 bayestestR
 changedate
 checkmark
-ci
 codecov
 conf
+df
 disgustingness
 easystats
 effectsize

diff --git a/man/expr_oneway_anova.Rd b/man/expr_oneway_anova.Rd
diff --git a/man/expr_template.Rd b/man/expr_template.Rd
diff --git a/tests/testthat/test-expr_contingency_tab_bayes.R b/tests/testthat/test-expr_contingency_tab_bayes.R
@@ -97,10 +97,9 @@ test_that(
         counts = "Freq",
         sampling.plan = "jointMulti",
         fixed.margin = "rows",
-        k = 3L,
-        output = "expression",
         conf.level = 0.99,
-        centrality = "mean"
+        k = 3L,
+        output = "expression"
       )
 
     # with counts
@@ -123,7 +122,7 @@ test_that(
       ggplot2::expr(
         paste(
           "log"["e"] * "(BF"["01"] * ") = " * "-3.335" * ", ",
-          widehat(italic("V"))["median"]^"posterior" * " = " * "0.479" * ", ",
+          widehat(italic("V"))["Cramer"]^"posterior" * " = " * "0.479" * ", ",
           "CI"["89%"]^"HDI" * " [" * "0.285" * ", " * "0.692" * "], ",
           italic("a")["Gunel-Dickey"] * " = " * "1.000"
         )
@@ -138,7 +137,7 @@ test_that(
       ggplot2::expr(
         paste(
           "log"["e"] * "(BF"["01"] * ") = " * "-214.255" * ", ",
-          widehat(italic("V"))["median"]^"posterior" * " = " * "0.455" * ", ",
+          widehat(italic("V"))["Cramer"]^"posterior" * " = " * "0.455" * ", ",
           "CI"["99%"]^"HDI" * " [" * "0.402" * ", " * "0.508" * "], ",
           italic("a")["Gunel-Dickey"] * " = " * "1.000"
         )
@@ -150,7 +149,7 @@ test_that(
       ggplot2::expr(
         paste(
           "log"["e"] * "(BF"["01"] * ") = " * "-213.873" * ", ",
-          widehat(italic("V"))["median"]^"posterior" * " = " * "0.454" * ", ",
+          widehat(italic("V"))["Cramer"]^"posterior" * " = " * "0.454" * ", ",
           "CI"["95%"]^"HDI" * " [" * "0.417" * ", " * "0.495" * "], ",
           italic("a")["Gunel-Dickey"] * " = " * "1.500"
         )