Merge branch 'main' into check_reliability

Author: strengejacke

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: performance
 Title: Assessment of Regression Models Performance
-Version: 0.13.0.2
+Version: 0.13.0.3
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",

R/binned_residuals.R

@@ -80,13 +80,19 @@ binned_residuals <- function(model,
                              n_bins = NULL,
                              show_dots = NULL,
                              ci = 0.95,
-                             ci_type = c("exact", "gaussian", "boot"),
-                             residuals = c("deviance", "pearson", "response"),
+                             ci_type = "exact",
+                             residuals = "deviance",
                              iterations = 1000,
                              verbose = TRUE,
                              ...) {
-  ci_type <- match.arg(ci_type)
-  residuals <- match.arg(residuals)
+  ci_type <- insight::validate_argument(
+    ci_type,
+    c("exact", "gaussian", "boot")
+  )
+  residuals <- insight::validate_argument(
+    residuals,
+    c("deviance", "pearson", "response")
+  )
 
   # for non-bernoulli models, `"exact"` doesn't work
   if (isFALSE(insight::model_info(model)$is_bernoulli)) {

R/check_collinearity.R

@@ -305,55 +305,70 @@ check_collinearity.betamfx <- check_collinearity.logitor
 #' @rdname check_collinearity
 #' @export
 check_collinearity.glmmTMB <- function(x,
-                                       component = c("all", "conditional", "count", "zi", "zero_inflated"),
+                                       component = "all",
                                        ci = 0.95,
                                        verbose = TRUE,
                                        ...) {
-  component <- match.arg(component)
+  component <- insight::validate_argument(
+    component,
+    c("all", "conditional", "count", "zi", "zero_inflated")
+  )
   .check_collinearity_zi_model(x, component, ci = ci, verbose = verbose)
 }
 
 
 #' @export
 check_collinearity.MixMod <- function(x,
-                                      component = c("all", "conditional", "count", "zi", "zero_inflated"),
+                                      component = "all",
                                       ci = 0.95,
                                       verbose = TRUE,
                                       ...) {
-  component <- match.arg(component)
+  component <- insight::validate_argument(
+    component,
+    c("all", "conditional", "count", "zi", "zero_inflated")
+  )
   .check_collinearity_zi_model(x, component, ci = ci, verbose = verbose)
 }
 
 
 #' @export
 check_collinearity.hurdle <- function(x,
-                                      component = c("all", "conditional", "count", "zi", "zero_inflated"),
+                                      component = "all",
                                       ci = 0.95,
                                       verbose = verbose,
                                       ...) {
-  component <- match.arg(component)
+  component <- insight::validate_argument(
+    component,
+    c("all", "conditional", "count", "zi", "zero_inflated")
+  )
   .check_collinearity_zi_model(x, component, ci = ci, verbose = verbose)
 }
 
 
 #' @export
 check_collinearity.zeroinfl <- function(x,
-                                        component = c("all", "conditional", "count", "zi", "zero_inflated"),
+                                        component = "all",
                                         ci = 0.95,
                                         verbose = verbose,
                                         ...) {
-  component <- match.arg(component)
+  component <- insight::validate_argument(
+    component,
+    c("all", "conditional", "count", "zi", "zero_inflated")
+  )
   .check_collinearity_zi_model(x, component, ci = ci, verbose = verbose)
 }
 
 
 #' @export
 check_collinearity.zerocount <- function(x,
-                                         component = c("all", "conditional", "count", "zi", "zero_inflated"),
+                                         component = "all",
                                          ci = 0.95,
                                          verbose = verbose,
                                          ...) {
-  component <- match.arg(component)
+  component <- insight::validate_argument(
+    component,
+    c("all", "conditional", "count", "zi", "zero_inflated")
+  )
   .check_collinearity_zi_model(x, component, ci = ci, verbose = verbose)
 }
 

R/check_dag.R

@@ -215,14 +215,17 @@ check_dag <- function(...,
                       exposure = NULL,
                       adjusted = NULL,
                       latent = NULL,
-                      effect = c("all", "total", "direct"),
+                      effect = "all",
                       coords = NULL) {
   insight::check_if_installed(
     c("ggdag", "dagitty"),
     reason = "to check correct adjustments for identifying causal effects."
   )
 
-  effect <- match.arg(effect)
+  effect <- insight::validate_argument(
+    effect,
+    c("all", "total", "direct")
+  )
 
   # retrieve formulas
   formulas <- list(...)

R/check_homogeneity.R

@@ -30,16 +30,19 @@
 #' result <- check_homogeneity(model)
 #' plot(result)
 #' @export
-check_homogeneity <- function(x, method = c("bartlett", "fligner", "levene", "auto"), ...) {
+check_homogeneity <- function(x, method = "bartlett", ...) {
   UseMethod("check_homogeneity")
 }
 
 
 # default -------------------------
 
 #' @export
-check_homogeneity.default <- function(x, method = c("bartlett", "fligner", "levene", "auto"), ...) {
-  method <- match.arg(method)
+check_homogeneity.default <- function(x, method = "bartlett", ...) {
+  method <- insight::validate_argument(
+    method,
+    c("bartlett", "fligner", "levene", "auto")
+  )
 
   resp <- insight::find_response(x)
   pred <- insight::find_predictors(x, component = "conditional", flatten = TRUE)

R/check_normality.R

@@ -189,9 +189,9 @@ print.check_normality <- function(x, ...) {
 
 #' @rdname check_normality
 #' @export
-check_normality.merMod <- function(x, effects = c("fixed", "random"), ...) {
+check_normality.merMod <- function(x, effects = "fixed", ...) {
   # args
-  effects <- match.arg(effects)
+  effects <- insight::validate_argument(effects, c("fixed", "random"))
   info <- insight::model_info(x)
 
   # valid model?

R/check_outliers.R

@@ -1489,8 +1489,8 @@ check_outliers.metabin <- check_outliers.metagen
 #' @rdname check_outliers
 #' @export
 check_outliers.performance_simres <- function(x, type = "default", iterations = 100, alternative = "two.sided", ...) {
-  type <- match.arg(type, c("default", "binomial", "bootstrap"))
-  alternative <- match.arg(alternative, c("two.sided", "greater", "less"))
+  type <- insight::validate_argument(type, c("default", "binomial", "bootstrap"))
+  alternative <- insight::validate_argument(alternative, c("two.sided", "greater", "less"))
 
   insight::check_if_installed("DHARMa")
   result <- DHARMa::testOutliers(x, type = type, nBoot = iterations, alternative = alternative, plot = FALSE, ...)

R/check_overdispersion.R

@@ -284,8 +284,11 @@ check_overdispersion.glmmTMB <- check_overdispersion.merMod
 
 #' @rdname check_overdispersion
 #' @export
-check_overdispersion.performance_simres <- function(x, alternative = c("two.sided", "less", "greater"), ...) {
-  alternative <- match.arg(alternative)
+check_overdispersion.performance_simres <- function(x, alternative = "two.sided", ...) {
+  alternative <- insight::validate_argument(
+    alternative,
+    c("two.sided", "less", "greater")
+  )
 
   # check for special arguments - we may pass "object_name" from other methods
   dots <- list(...)

R/check_predictions.R

@@ -126,7 +126,10 @@ check_predictions.default <- function(object,
   }
 
   # args
-  type <- match.arg(type, choices = c("density", "discrete_dots", "discrete_interval", "discrete_both"))
+  type <- insight::validate_argument(
+    type,
+    c("density", "discrete_dots", "discrete_interval", "discrete_both")
+  )
 
   pp_check.lm(
     object,
@@ -161,7 +164,10 @@ check_predictions.stanreg <- function(object,
   }
 
   # args
-  type <- match.arg(type, choices = c("density", "discrete_dots", "discrete_interval", "discrete_both"))
+  type <- insight::validate_argument(
+    type,
+    c("density", "discrete_dots", "discrete_interval", "discrete_both")
+  )
 
   # convert to type-argument for pp_check
   pp_type <- switch(type,

R/check_residuals.R

@@ -8,7 +8,8 @@
 #' @param x An object returned by [`simulate_residuals()`] or
 #' [`DHARMa::simulateResiduals()`].
 #' @param alternative A character string specifying the alternative hypothesis.
-#' See [`stats::ks.test()`] for details.
+#' Can be one of `"two.sided"`, `"less"`, or `"greater"`. See
+#' [`stats::ks.test()`] for details.
 #' @param ... Passed down to [`stats::ks.test()`].
 #'
 #' @details Uniformity of residuals is checked using a Kolmogorov-Smirnov test.
@@ -38,7 +39,7 @@ check_residuals <- function(x, ...) {
 
 #' @rdname check_residuals
 #' @export
-check_residuals.default <- function(x, alternative = c("two.sided", "less", "greater"), ...) {
+check_residuals.default <- function(x, alternative = "two.sided", ...) {
   if (insight::is_model(x)) {
     check_residuals(simulate_residuals(x, ...), alternative = alternative)
   } else {
@@ -47,8 +48,11 @@ check_residuals.default <- function(x, alternative = c("two.sided", "less", "gre
 }
 
 #' @export
-check_residuals.performance_simres <- function(x, alternative = c("two.sided", "less", "greater"), ...) {
-  alternative <- match.arg(alternative)
+check_residuals.performance_simres <- function(x, alternative = "two.sided", ...) {
+  alternative <- insight::validate_argument(
+    alternative,
+    c("two.sided", "less", "greater")
+  )
   ts_test <- suppressWarnings(
     stats::ks.test(
       stats::residuals(x),