minor revisions (#1089)

* minor revisions

* paper

* skip on CI

* Update DESCRIPTION

* update tests

Author: strengejacke

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.24.2.15
+Version: 0.24.2.16
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -80,7 +80,7 @@ Depends:
 Imports:
     bayestestR (>= 0.15.2),
     datawizard (>= 1.0.2),
-    insight (>= 1.1.0),
+    insight (>= 1.2.0),
     graphics,
     methods,
     stats,
@@ -224,5 +224,6 @@ Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3
 Config/testthat/parallel: true
 Config/Needs/website: easystats/easystatstemplate
+Config/Needs/check: stan-dev/cmdstanr
 Config/rcmdcheck/ignore-inconsequential-notes: true
 Remotes: easystats/insight, easystats/bayestestR

NEWS.md

@@ -9,6 +9,8 @@
 * `model_parameters()` now shows a more informative coefficient name for binomial
   models with probit-link.
 
+* Argument `wb_component` now defaults to `FALSE`.
+
 ## Bug fixes
 
 * Fixed printing issue with `model_parameters()` for `htest` objects when

R/methods_glmmTMB.R

@@ -171,7 +171,7 @@ model_parameters.glmmTMB <- function(model,
                                      group_level = FALSE,
                                      exponentiate = FALSE,
                                      p_adjust = NULL,
-                                     wb_component = TRUE,
+                                     wb_component = FALSE,
                                      include_info = getOption("parameters_mixed_info", FALSE),
                                      include_sigma = FALSE,
                                      keep = NULL,

R/methods_lme4.R

@@ -15,7 +15,7 @@ model_parameters.merMod <- function(model,
                                     p_adjust = NULL,
                                     vcov = NULL,
                                     vcov_args = NULL,
-                                    wb_component = TRUE,
+                                    wb_component = FALSE,
                                     include_info = getOption("parameters_mixed_info", FALSE),
                                     include_sigma = FALSE,
                                     keep = NULL,

R/utils_model_parameters.R

@@ -1,7 +1,9 @@
-# This function add meta-information to the returned parameters data frame,
-# usually used for printing etc.
-
+#' This function adds meta-information to the returned parameters data frame,
+#' usually used for printing etc. Prettifying names can be time consuming, if
+#' it is not necessary to have pretty names, set `pretty_names = FALSE`
+#'
 #' @keywords internal
+#' @noRd
 .add_model_parameters_attributes <- function(params,
                                              model,
                                              ci,
@@ -241,6 +243,12 @@
   )
 }
 
+
+#' This function formats the column name of the printed output, to reflect
+#' the correct type of coefficient.
+#'
+#' @keywords internal
+#' @noRd
 .find_coefficient_type <- function(info, exponentiate, model = NULL) {
   # column name for coefficients
   coef_col <- "Coefficient"
@@ -300,7 +308,11 @@
 }
 
 
+#' This function exponentiates coefficients, e.g. to return odds ratios instead
+#' of log-odds ratios.
+#'
 #' @keywords internal
+#' @noRd
 .exponentiate_parameters <- function(params, model = NULL, exponentiate = TRUE) {
   # "exponentiate" must be
   # - TRUE, will always exponentiate all coefficients
@@ -347,6 +359,12 @@
 }
 
 
+#' this function extract "prettified" parameter names, using
+#' `insight::clean_parameters()`, and matches them with the parameter names.
+#' the result is a named vector, added as attributes to the output
+#'
+#' @keywords internal
+#' @noRd
 .add_pretty_names <- function(params, model) {
   attr(params, "model_class") <- class(model)
   cp <- insight::clean_parameters(model)
@@ -437,10 +455,12 @@
 }
 
 
-# checks for valid inputs in model_parameters(). E.g., some models don't support
-# the "vcov" argument - this should not be silently ignored, but rather the user
-# should be informed that robust SE are not available for that model.
-
+#' checks for valid inputs in model_parameters(). E.g., some models don't support
+#' the "vcov" argument - this should not be silently ignored, but rather the user
+#' should be informed that robust SE are not available for that model.
+#'
+#' @keywords internal
+#' @noRd
 .check_dots <- function(dots, not_allowed, model_class, function_name = "model_parameters", verbose = TRUE) {
   # remove arguments that are NULL
   dots <- insight::compact_list(dots)

man/model_parameters.glmmTMB.Rd

@@ -54,7 +54,7 @@ @article{lakens2020equivalence
 	title = {Equivalence Testing for Psychological Research: A Tutorial},
 	volume = {1},
 	issn = {2515-2459, 2515-2467},
-	url = {http://journals.sagepub.com/doi/10.1177/2515245918770963},
+	url = {https://journals.sagepub.com/doi/10.1177/2515245918770963},
 	doi = {10.1177/2515245918770963},
 	language = {en},
 	number = {2},

paper/paper.bib

@@ -1,7 +1,7 @@
-# print-model_parameters
+# print-model_parameters-1
 
     Code
-      model_parameters(model, effects = "fixed")
+      model_parameters(model, effects = "fixed", wb_component = TRUE)
     Output
       Parameter   | Coefficient |   SE |         95% CI | t(558) |      p
       -------------------------------------------------------------------
@@ -27,7 +27,25 @@
 ---
 
     Code
-      model_parameters(m1, effects = "all")
+      model_parameters(model, effects = "fixed", wb_component = FALSE)
+    Output
+      # Fixed Effects
+      
+      Parameter    | Coefficient |   SE |         95% CI | t(558) |      p
+      --------------------------------------------------------------------
+      (Intercept)  |       71.53 | 1.56 | [68.48, 74.59] |  45.98 | < .001
+      time         |        1.09 | 0.64 | [-0.17,  2.34] |   1.70 | 0.089 
+      phq4 within  |       -3.66 | 0.41 | [-4.46, -2.86] |  -8.95 | < .001
+      phq4 between |       -6.28 | 0.50 | [-7.27, -5.30] | -12.53 | < .001
+    Message
+      
+      Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
+        using a Wald t-distribution approximation.
+
+# print-model_parameters-2
+
+    Code
+      model_parameters(m1, effects = "all", wb_component = TRUE)
     Output
       # Fixed Effects
       
@@ -52,7 +70,53 @@
 ---
 
     Code
-      model_parameters(m1, effects = "fixed", include_info = TRUE)
+      model_parameters(m1, effects = "all", wb_component = FALSE)
+    Output
+      # Fixed Effects
+      
+      Parameter   | Coefficient |   SE |        95% CI | t(28) |      p
+      -----------------------------------------------------------------
+      (Intercept) |        0.65 | 0.50 | [-0.38, 1.68] |  1.29 | 0.206 
+      cyl         |        0.40 | 0.08 | [ 0.25, 0.56] |  5.29 | < .001
+      
+      # Random Effects
+      
+      Parameter            | Coefficient |   SE |       95% CI
+      --------------------------------------------------------
+      SD (Intercept: gear) |        0.27 | 0.24 | [0.05, 1.54]
+      SD (Residual)        |        0.59 | 0.08 | [0.46, 0.77]
+    Message
+      
+      Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
+        using a Wald t-distribution approximation. Uncertainty intervals for
+        random effect variances computed using a Wald z-distribution
+        approximation.
+
+---
+
+    Code
+      model_parameters(m1, effects = "fixed", include_info = TRUE, wb_component = TRUE)
+    Output
+      # Fixed Effects
+      
+      Parameter   | Coefficient |   SE |        95% CI | t(28) |      p
+      -----------------------------------------------------------------
+      (Intercept) |        0.65 | 0.50 | [-0.38, 1.68] |  1.29 | 0.206 
+      cyl         |        0.40 | 0.08 | [ 0.25, 0.56] |  5.29 | < .001
+      
+      Model: wt ~ cyl (32 Observations)
+      Sigma: 0.594 (df = 28)
+      RMSE : 0.564
+      Conditional R2: 0.628; Marginal R2: 0.550
+    Message
+      
+      Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
+        using a Wald t-distribution approximation.
+
+---
+
+    Code
+      model_parameters(m1, effects = "fixed", include_info = TRUE, wb_component = FALSE)
     Output
       # Fixed Effects
       

tests/testthat/_snaps/model_parameters.mixed.md

@@ -21,6 +21,7 @@ test_that("emmeans | lm", {
     tolerance = 0.1
   )
 
+  skip_on_ci()
   mp <- model_parameters(emmeans::emmeans(b, consec ~ cyl), verbose = FALSE)
   expect_identical(
     colnames(mp),

tests/testthat/test-bootstrap_emmeans.R

@@ -122,20 +122,25 @@ model <- lme4::lmer(
   QoL ~ time + phq4_within + phq4_between + (1 | ID),
   data = qol_cancer
 )
-mp <- model_parameters(model, effects = "fixed")
 
 test_that("model_parameters.mixed", {
+  mp <- model_parameters(model, effects = "fixed", wb_component = TRUE)
+  mp2 <- model_parameters(model, effects = "fixed", wb_component = FALSE)
   expect_identical(mp$Component, c("rewb-contextual", "rewb-contextual", "within", "between"))
+  expect_null(mp2$Component)
 })
 
 
-test_that("print-model_parameters", {
-  expect_snapshot(model_parameters(model, effects = "fixed"))
+test_that("print-model_parameters-1", {
+  expect_snapshot(model_parameters(model, effects = "fixed", wb_component = TRUE))
+  expect_snapshot(model_parameters(model, effects = "fixed", wb_component = FALSE))
 })
 
-test_that("print-model_parameters", {
+test_that("print-model_parameters-2", {
   skip_if_not_installed("merDeriv")
-  expect_snapshot(model_parameters(m1, effects = "all"))
+  expect_snapshot(model_parameters(m1, effects = "all", wb_component = TRUE))
+  expect_snapshot(model_parameters(m1, effects = "all", wb_component = FALSE))
 
-  expect_snapshot(model_parameters(m1, effects = "fixed", include_info = TRUE))
+  expect_snapshot(model_parameters(m1, effects = "fixed", include_info = TRUE, wb_component = TRUE))
+  expect_snapshot(model_parameters(m1, effects = "fixed", include_info = TRUE, wb_component = FALSE))
 })