Merge pull request #7 from IndrajeetPatil/simplify_dataframe

simplify dataframe output

DESCRIPTION

@@ -24,6 +24,7 @@ Depends:
 Imports: 
     BayesFactor,
     dplyr,
+    insight (>= 0.9.6.1),
     ipmisc,
     metaBMA,
     parameters,
@@ -35,6 +36,8 @@ Suggests:
     rmarkdown,
     spelling,
     testthat
+Remotes:
+    easystats/insight    
 Encoding: UTF-8
 Language: en-US
 LazyData: true

NAMESPACE

@@ -33,13 +33,13 @@ importFrom(dplyr,pull)
 importFrom(dplyr,rename)
 importFrom(dplyr,select)
 importFrom(dplyr,tibble)
+importFrom(insight,standardize_names)
 importFrom(ipmisc,"%$%")
 importFrom(ipmisc,"%<-%")
 importFrom(ipmisc,"%<>%")
 importFrom(ipmisc,"%>%")
 importFrom(ipmisc,as_tibble)
 importFrom(ipmisc,blue)
-importFrom(ipmisc,easystats_to_tidy_names)
 importFrom(ipmisc,long_to_wide_converter)
 importFrom(ipmisc,red)
 importFrom(ipmisc,signif_column)

NEWS.md

@@ -4,6 +4,11 @@ BREAKING CHANGES
 
   - Removes the unnecessary aliases for certain tests: `bf_one_sample_ttest`,
     `bf_two_sample_ttest`, and `bf_onesample_proptest`.
+
+  - The output dataframe now only contains results for the alternative
+    hypothesis (`BF10`) and its `log` value to avoid cluttered dataframe since
+    all the other columns were essentially mathematical transformations of it
+    and not really relevant.
 
 MAJOR CHANGES
 

R/bf_contingency_tab.R

@@ -120,7 +120,7 @@ bf_contingency_tab <- function(data,
     data %<>% dplyr::mutate(.data = ., {{ y }} := droplevels(as.factor({{ y }})))
 
     # extracting results from Bayesian test and creating a dataframe
-    bf.df <-
+    df <-
       bf_extractor(
         BayesFactor::contingencyTableBF(
           x = table(data %>% dplyr::pull({{ x }}), data %>% dplyr::pull({{ y }})),
@@ -185,21 +185,22 @@ bf_contingency_tab <- function(data,
     pr_y_h1 <- BayesFactor::logMeanExpLogs(tmp_pr_h1)
 
     # computing Bayes Factor and formatting the results
-    bf.df <-
+    df <-
       tibble(bf10 = exp(pr_y_h1 - pr_y_h0)) %>%
-      bf_formatter(.) %>%
-      dplyr::mutate(.data = ., prior.concentration = prior.concentration)
+      dplyr::mutate(log_e_bf10 = log(bf10), prior.concentration = prior.concentration)
   }
 
   # ========================= caption preparation =============================
 
   # changing aspects of the caption based on what output is needed
   if (output %in% c("null", "caption", "H0", "h0")) {
-    bf.value <- bf.df$log_e_bf01[[1]]
-    bf.subscript <- "01"
+    # bf-related text
+    bf.value <- -log(df$bf10[[1]])
+    bf.sub <- "01"
   } else {
-    bf.value <- -bf.df$log_e_bf01[[1]]
-    bf.subscript <- "10"
+    # bf-related text
+    bf.value <- log(df$bf10[[1]])
+    bf.sub <- "10"
   }
 
   # final expression
@@ -209,27 +210,27 @@ bf_contingency_tab <- function(data,
         displaystyle(top.text),
         expr = paste(
           "log"["e"],
-          "(BF"[bf.subscript],
+          "(BF"[bf.sub],
           ") = ",
           bf,
           ", ",
-          italic("a"),
+          italic("a")["Gunel-Dickey"],
           " = ",
           a
         )
       ),
       env = list(
         top.text = caption,
-        bf.subscript = bf.subscript,
+        bf.sub = bf.sub,
         bf = specify_decimal_p(x = bf.value, k = k),
-        a = specify_decimal_p(x = bf.df$prior.concentration[[1]], k = k)
+        a = specify_decimal_p(x = df$prior.concentration[[1]], k = k)
       )
     )
 
   # return the text results or the dataframe with results
   return(switch(
     EXPR = output,
-    "results" = bf.df,
+    "results" = dplyr::select(df, -dplyr::matches("error|time|code")),
     bf_message
   ))
 }

R/bf_corr_test.R

@@ -21,6 +21,7 @@
 #' @examples
 #' # for reproducibility
 #' set.seed(123)
+#' library(tidyBF)
 #'
 #' # to see results
 #' bf_corr_test(

R/bf_meta.R

@@ -89,17 +89,17 @@ bf_meta <- function(data,
     dplyr::filter(.data = ., term == "d")
 
   # dataframe with bayes factors
-  bf.df <-
-    tibble(bf10 = meta_res$BF["random_H1", "random_H0"]) %>%
-    bf_formatter(.)
+  df <- tibble(bf10 = meta_res$BF["random_H1", "random_H0"])
 
   # changing aspects of the caption based on what output is needed
   if (output %in% c("null", "caption", "H0", "h0")) {
-    bf.value <- bf.df$log_e_bf01[[1]]
-    bf.subscript <- "01"
+    # bf-related text
+    bf.value <- -log(df$bf10[[1]])
+    bf.sub <- "01"
   } else {
-    bf.value <- bf.df$log_e_bf10[[1]]
-    bf.subscript <- "10"
+    # bf-related text
+    bf.value <- log(df$bf10[[1]])
+    bf.sub <- "10"
   }
 
   # prepare the Bayes factor message
@@ -108,7 +108,7 @@ bf_meta <- function(data,
       atop(displaystyle(top.text),
         expr = paste(
           "log"["e"],
-          "(BF"[bf.subscript],
+          "(BF"[bf.sub],
           ") = ",
           bf,
           ", ",
@@ -125,7 +125,7 @@ bf_meta <- function(data,
       ),
       env = list(
         top.text = caption,
-        bf.subscript = bf.subscript,
+        bf.sub = bf.sub,
         bf = specify_decimal_p(x = bf.value, k = k),
         d.pmean = specify_decimal_p(x = df_estimates$mean[[1]], k = k),
         d.pmean.LB = specify_decimal_p(x = df_estimates$hpd95_lower[[1]], k = k),
@@ -136,7 +136,7 @@ bf_meta <- function(data,
   # return the text results or the dataframe with results
   return(switch(
     EXPR = output,
-    "results" = bf.df,
+    "results" = df,
     bf_message
   ))
 }

R/bf_ttest.R

@@ -62,6 +62,17 @@ bf_ttest <- function(data,
   x <- rlang::ensym(x)
   y <- if (!rlang::quo_is_null(rlang::enquo(y))) rlang::ensym(y)
 
+  # -------------------------- one-sample tests ------------------------------
+
+  if (rlang::quo_is_null(rlang::enquo(y))) {
+    bf_object <-
+      BayesFactor::ttestBF(
+        x = stats::na.omit(data %>% dplyr::pull({{ x }})),
+        rscale = bf.prior,
+        mu = test.value
+      )
+  }
+
   # -------------------------- two-sample tests ------------------------------
 
   if (!rlang::quo_is_null(rlang::enquo(y))) {
@@ -77,14 +88,11 @@ bf_ttest <- function(data,
 
     # 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,
+          x = data[[2]],
+          y = data[[3]],
           rscale = bf.prior,
           paired = TRUE,
           progress = FALSE
@@ -105,18 +113,7 @@ bf_ttest <- function(data,
     }
   }
 
-  # -------------------------- one-sample tests ------------------------------
-
-  if (rlang::quo_is_null(rlang::enquo(y))) {
-    bf_object <-
-      BayesFactor::ttestBF(
-        x = stats::na.omit(data %>% dplyr::pull({{ x }})),
-        rscale = bf.prior,
-        mu = test.value
-      )
-  }
-
-  # ============================ return ==================================
+  # -------------------------- return --------------------------
 
   # return the text results or the dataframe with results
   switch(