Merge branch 'main' into support_coxme_ranef

Author: strengejacke

.Rbuildignore

@@ -20,6 +20,7 @@
 ^vignettes/p.
 ^vignettes/s.
 ^tests/_snaps/.
+^tests/testthat/_snaps/.
 ^cran-comments\.md$
 ^revdep$
 ^CODE_OF_CONDUCT\.md$

DESCRIPTION

@@ -1,12 +1,12 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.24.2.15
+Version: 0.26.0.2
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
              role = c("aut", "cre"),
-             email = "[email protected]",
+             email = "[email protected]",
              comment = c(ORCID = "0000-0002-8895-3206")),
       person(given = "Dominique",
              family = "Makowski",
@@ -78,9 +78,9 @@ BugReports: https://github.com/easystats/parameters/issues
 Depends:
     R (>= 3.6)
 Imports:
-    bayestestR (>= 0.15.2),
-    datawizard (>= 1.0.2),
-    insight (>= 1.1.0),
+    bayestestR (>= 0.16.0),
+    datawizard (>= 1.1.0),
+    insight (>= 1.3.0),
     graphics,
     methods,
     stats,
@@ -112,6 +112,7 @@ Suggests:
     coda,
     coxme,
     cplm,
+    curl,
     dbscan,
     did,
     distributional,
@@ -155,7 +156,7 @@ Suggests:
     logspline,
     lqmm,
     M3C,
-    marginaleffects (>= 0.25.0),
+    marginaleffects (>= 0.26.0),
     modelbased (>= 0.9.0),
     MASS,
     Matrix,
@@ -182,7 +183,7 @@ Suggests:
     panelr,
     pbkrtest,
     PCDimension,
-    performance (>= 0.12.0),
+    performance (>= 0.14.0),
     plm,
     PMCMRplus,
     poorman,
@@ -224,5 +225,6 @@ 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

NAMESPACE

@@ -310,6 +310,7 @@ S3method(model_parameters,pairwise.htest)
 S3method(model_parameters,pam)
 S3method(model_parameters,parameters_efa)
 S3method(model_parameters,parameters_pca)
+S3method(model_parameters,pb2)
 S3method(model_parameters,pgmm)
 S3method(model_parameters,poissonirr)
 S3method(model_parameters,poissonmfx)

NEWS.md

@@ -1,4 +1,29 @@
-# parameters (devel)
+# parameters 0.26.0
+
+## Changes
+
+* The `effects` argument in `model_parameters()` for classes `merMod`, `glmmTMB`,
+  `brmsfit` and `stanreg` gets an additional `"grouplevel"` option, to return
+  the group-level estimates for random effects.
+
+* `model_parameters()` for Anova-objects gains a `p_adjust` argument, to apply
+  p-adjustment where possible. Furthermore, for models from package *afex*, where
+  p-adjustment was applied during model-fitting, the correct p-values are now
+  returned (before, unadjusted p-values were returned in some cases).
+
+* Revised code-base to address changes in latest *insight* update. Dealing with
+  larger models (many parameters, many posterior samples) from packages *brms*
+  and *rstanarm* is more efficient now. Furthermore, the options for the
+  `effects` argument have a new behaviour. `"all"` only returns fixed effects
+  and random effects variance components, but no longer the group level
+  estimates. Use `effects = "full"` to return all parameters. This change is
+  mainly to be more flexible and gain more efficiency for models with many
+  parameters and / or many posterior draws.
+
+* `model_parameters()` for Anova objects gains an `include_intercept` argument,
+  to include intercepts in the Anova table, where possible.
+
+# parameters 0.25.0
 
 ## Changes
 
@@ -9,11 +34,18 @@
 * `model_parameters()` now shows a more informative coefficient name for binomial
   models with probit-link.
 
+* Argument `wb_component` now defaults to `FALSE`.
+
+* Improved support and printing for tests from package *WRS2*.
+
 ## Bug fixes
 
 * Fixed printing issue with `model_parameters()` for `htest` objects when
   printing into markdown or HTML format.
 
+* Fixed printing issue with `model_parameters()` for mixed models when
+  `include_reference = TRUE`.
+
 # parameters 0.24.2
 
 ## Changes

R/1_model_parameters.R

@@ -129,7 +129,7 @@
 #'
 #' - **pseudo** (*for 2-level (G)LMMs only*): In this (post-hoc) method, the
 #' response and the predictor are standardized based on the level of prediction
-#' (levels are detected with [performance::check_heterogeneity_bias()]): Predictors
+#' (levels are detected with [performance::check_group_variation()]): Predictors
 #' are standardized based on their SD at level of prediction (see also
 #' [datawizard::demean()]); The outcome (in linear LMMs) is standardized based
 #' on a fitted random-intercept-model, where `sqrt(random-intercept-variance)`
@@ -438,14 +438,17 @@ parameters <- model_parameters
 #'   `"pseudo"`. See 'Details' in [`standardize_parameters()`].
 #'   **Importantly**:
 #'   - The `"refit"` method does *not* standardize categorical predictors (i.e.
-#'   factors), which may be a different behaviour compared to other R packages
-#'   (such as **lm.beta**) or other software packages (like SPSS). to mimic
-#'   such behaviours, either use `standardize="basic"` or standardize the data
-#'   with `datawizard::standardize(force=TRUE)` *before* fitting the model.
+#'     factors), which may be a different behaviour compared to other R packages
+#'     (such as **lm.beta**) or other software packages (like SPSS). to mimic
+#'     such behaviours, either use `standardize="basic"` or standardize the data
+#'     with `datawizard::standardize(force=TRUE)` *before* fitting the model.
+#'   - By default, the response (dependent) variable is also standardized, *if
+#'     applicable*. Set `include_response = FALSE` to avoid standardization of
+#'     the response variable. See details in [`datawizard::standardize.default()`].
 #'   - For mixed models, when using methods other than `"refit"`, only the fixed
-#'   effects will be standardized.
+#'     effects will be standardized.
 #'   - Robust estimation (i.e., `vcov` set to a value other than `NULL`) of
-#'   standardized parameters only works when `standardize="refit"`.
+#'     standardized parameters only works when `standardize="refit"`.
 #' @param exponentiate Logical, indicating whether or not to exponentiate the
 #'   coefficients (and related confidence intervals). This is typical for
 #'   logistic regression, or more generally speaking, for models with log or

R/compare_parameters.R

@@ -169,7 +169,7 @@ compare_parameters <- function(...,
       dat <- model
     } else {
       # set default-ci_type for Bayesian models
-      if (.is_bayesian_model(model, exclude = c("bmerMod", "bayesx", "blmerMod", "bglmerMod")) && !ci_method %in% c("hdi", "quantile", "ci", "eti", "si", "bci", "bcai")) { # nolint
+      if (insight::is_bayesian_model(model, exclude = c("bmerMod", "bayesx", "blmerMod", "bglmerMod")) && !ci_method %in% c("hdi", "quantile", "ci", "eti", "si", "bci", "bcai")) { # nolint
         ci_method_tmp <- "eti"
       } else {
         ci_method_tmp <- ci_method
@@ -305,19 +305,3 @@ compare_models <- compare_parameters
   }
   x
 }
-
-
-.is_bayesian_model <- function(x, exclude = NULL) {
-  bayes_classes <- c(
-    "brmsfit", "stanfit", "MCMCglmm", "stanreg",
-    "stanmvreg", "bmerMod", "BFBayesFactor", "bamlss",
-    "bayesx", "mcmc", "bcplm", "bayesQR", "BGGM",
-    "meta_random", "meta_fixed", "meta_bma", "blavaan",
-    "blrm", "blmerMod"
-  )
-  # if exclude is not NULL, remove elements in exclude from bayes_class
-  if (!is.null(exclude)) {
-    bayes_classes <- bayes_classes[!bayes_classes %in% exclude]
-  }
-  inherits(x, bayes_classes)
-}

R/display.R

@@ -105,7 +105,9 @@ display.parameters_model <- function(object,
                                      include_reference = FALSE,
                                      verbose = TRUE,
                                      ...) {
-  if (identical(format, "html")) {
+  format <- insight::validate_argument(format, c("markdown", "html", "md", "tt"))
+
+  if (format %in% c("html", "tt")) {
     print_html(
       x = object, pretty_names = pretty_names, split_components = split_components,
       select = select, digits = digits, caption = caption, subtitle = subtitle,
@@ -151,7 +153,9 @@ display.compare_parameters <- function(object,
                                        line_padding = 4,
                                        zap_small = FALSE,
                                        ...) {
-  if (identical(format, "html")) {
+  format <- insight::validate_argument(format, c("markdown", "html", "md", "tt"))
+
+  if (format %in% c("html", "tt")) {
     print_html(
       x = object, digits = digits, ci_digits = ci_digits, p_digits = p_digits,
       select = select, column_labels = column_labels, font_size = font_size,