minor tweaks

Author: strengejacke

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.24.2.19
+Version: 0.24.2.20
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",

R/methods_BayesFactor.R

@@ -245,7 +245,7 @@ model_parameters.BFBayesFactor <- function(model,
 
 #' @export
 p_value.BFBayesFactor <- function(model, ...) {
-  p <- bayestestR::p_direction(model)
+  p <- bayestestR::p_direction(model, ...)
   .data_frame(
     Parameter = .remove_backticks_from_string(p$Parameter),
     p = sapply(p$pd, bayestestR::convert_pd_to_p, simplify = TRUE)

R/methods_brms.R

@@ -123,13 +123,8 @@ model_parameters.brmsfit <- function(model,
     return(params)
   } else {
 
-    ## TODO: remove this once insight > 1.2.0 is on CRAN
-    if (utils::packageVersion("insight") > "1.2.0" && effects == "random") {
-      if (group_level) {
-        effects <- "grouplevel"
-      } else {
-        effects <- "random_variance"
-      }
+    if (utils::packageVersion("insight") > "1.2.0" && effects == "random" && group_level) {
+      effects <- "grouplevel"
     }
 
     # Processing
@@ -312,6 +307,9 @@ standard_error.brmsfit <- function(model,
                                    effects = "fixed",
                                    component = "all",
                                    ...) {
+
+  ## TODO: remove validation of effects and component once insight > 1.2.0 is on CRAN
+
   effects <- insight::validate_argument(
     effects,
     c("fixed", "random")

R/methods_rstanarm.R

@@ -26,6 +26,10 @@ model_parameters.stanreg <- function(model,
     return(params)
   }
 
+  if (utils::packageVersion("insight") > "1.2.0" && effects == "random" && group_level) {
+    effects <- "grouplevel"
+  }
+
   # Processing
   params <- .extract_parameters_bayesian(
     model,
@@ -47,6 +51,7 @@ model_parameters.stanreg <- function(model,
     ...
   )
 
+  ## TODO: remove this once insight > 1.2.0 on CRAN
   if (effects != "fixed") {
     random_effect_levels <- which(
       params$Effects == "random" & !startsWith(params$Parameter, "Sigma[")
@@ -99,6 +104,10 @@ model_parameters.stanmvreg <- function(model,
                                        drop = NULL,
                                        verbose = TRUE,
                                        ...) {
+  if (utils::packageVersion("insight") > "1.2.0" && effects == "random" && group_level) {
+    effects <- "grouplevel"
+  }
+
   # Processing
   params <- .extract_parameters_bayesian(
     model,