Clean up deprecated args, lintr

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.21.7.1
+Version: 0.21.7.2
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -218,4 +218,4 @@ Config/Needs/website:
     r-lib/pkgdown,
     easystats/easystatstemplate
 Config/rcmdcheck/ignore-inconsequential-notes: true
-Remotes: easystats/insight, easystats/datawizard, easystats/performance, easystats/bayestestR
+Remotes: easystats/insight, easystats/datawizard, easystats/performance, easystats/bayestestR, easystats/effectsize

NEWS.md

@@ -1,3 +1,10 @@
+# parameters 0.21.8
+
+## Breaking changes
+
+* Deprecated arguments in `model_parameters()` for `htest`, `aov` and
+  `BFBayesFactor` objects were removed.
+
 # parameters 0.21.7
 
 ## Changes

R/dof_kenward.R

@@ -263,7 +263,7 @@ dof_kenward <- function(model) {
 
   Gp <- lme4::getME(model, "Gp")
   n.RT <- length(Gp) - 1 ## Number of random terms (i.e. of (|)'s)
-  n.lev.by.RT <- sapply(lme4::getME(model, "flist"), function(x) length(levels(x)))
+  n.lev.by.RT <- sapply(lme4::getME(model, "flist"), nlevels)
   n.comp.by.RT <- .get.RT.dim.by.RT(model)
   n.parm.by.RT <- (n.comp.by.RT + 1) * n.comp.by.RT / 2
   n.RE.by.RT <- diff(Gp)

R/methods_BayesFactor.R

@@ -13,7 +13,6 @@
 #' @inheritParams bayestestR::describe_posterior
 #' @inheritParams p_value
 #' @inheritParams model_parameters.htest
-#' @param cohens_d,cramers_v Deprecated. Please use `effectsize_type`.
 #'
 #' @details
 #' The meaning of the extracted parameters:
@@ -29,24 +28,26 @@
 #'   the *g* parameters; See the *Bayes Factors for ANOVAs* paper
 #'   (\doi{10.1016/j.jmp.2012.08.001}).
 #'
-#' @examples
+#' @examplesIf require("BayesFactor")
 #' \donttest{
-#' if (require("BayesFactor")) {
-#'   # Bayesian t-test
-#'   model <- ttestBF(x = rnorm(100, 1, 1))
-#'   model_parameters(model)
-#'   model_parameters(model, cohens_d = TRUE, ci = .9)
+#' # Bayesian t-test
+#' model <- BayesFactor::ttestBF(x = rnorm(100, 1, 1))
+#' model_parameters(model)
+#' model_parameters(model, effectsize_type = "cohens_d", ci = 0.9)
 #'
-#'   # Bayesian contingency table analysis
-#'   data(raceDolls)
-#'   bf <- contingencyTableBF(raceDolls, sampleType = "indepMulti", fixedMargin = "cols")
-#'   model_parameters(bf,
-#'     centrality = "mean",
-#'     dispersion = TRUE,
-#'     verbose = FALSE,
-#'     effectsize_type = "cramers_v"
-#'   )
-#' }
+#' # Bayesian contingency table analysis
+#' data(raceDolls)
+#' bf <- BayesFactor::contingencyTableBF(
+#'   raceDolls,
+#'   sampleType = "indepMulti",
+#'   fixedMargin = "cols"
+#' )
+#' model_parameters(bf,
+#'   centrality = "mean",
+#'   dispersion = TRUE,
+#'   verbose = FALSE,
+#'   effectsize_type = "cramers_v"
+#' )
 #' }
 #' @return A data frame of indices related to the model's parameters.
 #' @export
@@ -62,16 +63,9 @@
                                            effectsize_type = NULL,
                                            include_proportions = FALSE,
                                            verbose = TRUE,
-                                           cohens_d = NULL,
-                                           cramers_v = NULL,
                                            ...) {
   insight::check_if_installed("BayesFactor")
 
-  ## TODO: remove in a later update
-  # handle deprected arguments ------
-  if (!is.null(cramers_v)) effectsize_type <- "cramers_v"
-  if (!is.null(cohens_d)) effectsize_type <- "cohens_d"
-
   if (any(startsWith(names(model@numerator), "Null"))) {
     if (isTRUE(verbose)) {
       insight::format_alert(
@@ -121,7 +115,7 @@
   tryCatch(
     {
       bfm <- as.data.frame(bayestestR::bayesfactor_models(model)[-1, ])
       if (!is.null(bfm$log_BF)) {
         out$BF <- exp(bfm$log_BF)
       } else {
         out$BF <- bfm$BF

R/methods_DirichletReg.R

@@ -21,20 +21,22 @@
 
   ## TODO check merge by
 
-  junk <- utils::capture.output(out <- .model_parameters_generic( # nolint
-    model = model,
-    ci = ci,
-    component = component,
-    bootstrap = bootstrap,
-    iterations = iterations,
-    merge_by = merge_by,
-    standardize = standardize,
-    exponentiate = exponentiate,
-    p_adjust = p_adjust,
-    keep_parameters = keep,
-    drop_parameters = drop,
-    ...
-  ))
+  junk <- utils::capture.output({
+    out <- .model_parameters_generic(
+      model = model,
+      ci = ci,
+      component = component,
+      bootstrap = bootstrap,
+      iterations = iterations,
+      merge_by = merge_by,
+      standardize = standardize,
+      exponentiate = exponentiate,
+      p_adjust = p_adjust,
+      keep_parameters = keep,
+      drop_parameters = drop,
+      ...
+    )
+  })
 
   out$Response[is.na(out$Response)] <- ""
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
@@ -78,7 +80,7 @@
     SE = as.vector(model$se)
   )
 
   if (!is.null(params$Component)) {
     out$Component <- params$Component
   } else {
     component <- "all"
@@ -119,7 +121,7 @@
     p = as.vector(2 * stats::pnorm(-abs(params$Estimate / model$se)))
   )
 
   if (!is.null(params$Component)) {
     out$Component <- params$Component
   } else {
     component <- "all"

R/methods_aov.R

@@ -35,7 +35,6 @@
 #'   (e.g., `"g"`, `"l"`, `"two"`...). See section *One-Sided CIs* in
 #'   the [effectsize_CIs vignette](https://easystats.github.io/effectsize/).
 #' @inheritParams model_parameters.default
-#' @param omega_squared,eta_squared,epsilon_squared Deprecated. Please use `effectsize_type`.
 #' @param ... Arguments passed to [`effectsize::effectsize()`]. For example,
 #'   to calculate _partial_ effect sizes types, use `partial = TRUE`. For objects
 #'   of class `htest` or `BFBayesFactor`, `adjust = TRUE` can be used to return
@@ -110,34 +109,7 @@
                                  drop = NULL,
                                  table_wide = FALSE,
                                  verbose = TRUE,
-                                 omega_squared = NULL,
-                                 eta_squared = NULL,
-                                 epsilon_squared = NULL,
                                  ...) {
-  ## TODO: remove in a later update
-  # handle deprected arguments ------
-  if (!is.null(omega_squared)) {
-    insight::format_warning(
-      "Argument `omega_squared` is deprecated.",
-      "Please use `effectsize_type = \"omega\"` instead."
-    )
-    effectsize_type <- "omega"
-  }
-  if (!is.null(eta_squared)) {
-    insight::format_warning(
-      "Argument `eta_squared` is deprecated.",
-      "Please use `effectsize_type = \"eta\"` instead."
-    )
-    effectsize_type <- "eta"
-  }
-  if (!is.null(epsilon_squared)) {
-    insight::format_warning(
-      "Argument `epsilon_squared` is deprecated.",
-      "Please use `effectsize_type = \"epsilon\"` instead."
-    )
-    effectsize_type <- "epsilon"
-  }
-
   # save model object, for later checks
   original_model <- model
   object_name <- insight::safe_deparse_symbol(substitute(model))
@@ -432,7 +404,7 @@
     predictors <- .safe(insight::get_predictors(model))
 
     # if data available, check contrasts and mean centering
     if (!is.null(predictors)) {
       treatment_contrasts_or_not_centered <- vapply(predictors, function(i) {
         if (is.factor(i)) {
           cn <- stats::contrasts(i)