From e7d3eadc177d318bb51a37026f3bc9c13a9d30da Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 9 Jun 2024 09:34:42 +0200
Subject: [PATCH] Fix #978

---
 R/methods_BayesFactor.R                       | 17 ++++++---
 R/methods_aov.R                               | 34 ++++++++++-------
 R/methods_htest.R                             | 37 +++++++++++--------
 R/methods_other.R                             | 11 +++++-
 man/model_parameters.BFBayesFactor.Rd         | 11 ++++--
 man/model_parameters.aov.Rd                   | 17 +++++----
 man/model_parameters.cgam.Rd                  |  7 +++-
 man/model_parameters.htest.Rd                 | 15 +++++---
 .../test-model_parameters.BFBayesFactor.R     |  4 +-
 tests/testthat/test-model_parameters.anova.R  |  2 +-
 tests/testthat/test-model_parameters.aov.R    |  6 +--
 .../test-model_parameters.aov_es_ci.R         | 20 +++++-----
 tests/testthat/test-model_parameters.htest.R  |  6 +--
 vignettes/model_parameters.Rmd                |  4 +-
 14 files changed, 116 insertions(+), 75 deletions(-)

diff --git a/R/methods_BayesFactor.R b/R/methods_BayesFactor.R
index ee21c8f56..72d96dd32 100644
--- a/R/methods_BayesFactor.R
+++ b/R/methods_BayesFactor.R
@@ -33,7 +33,7 @@
 #' # Bayesian t-test
 #' model <- BayesFactor::ttestBF(x = rnorm(100, 1, 1))
 #' model_parameters(model)
-#' model_parameters(model, effectsize_type = "cohens_d", ci = 0.9)
+#' model_parameters(model, es_type = "cohens_d", ci = 0.9)
 #'
 #' # Bayesian contingency table analysis
 #' data(raceDolls)
@@ -46,7 +46,7 @@
 #'   centrality = "mean",
 #'   dispersion = TRUE,
 #'   verbose = FALSE,
-#'   effectsize_type = "cramers_v"
+#'   es_type = "cramers_v"
 #' )
 #' }
 #' @return A data frame of indices related to the model's parameters.
@@ -60,9 +60,10 @@ model_parameters.BFBayesFactor <- function(model,
                                            rope_range = "default",
                                            rope_ci = 0.95,
                                            priors = TRUE,
-                                           effectsize_type = NULL,
+                                           es_type = NULL,
                                            include_proportions = FALSE,
                                            verbose = TRUE,
+                                           effectsize_type = NULL,
                                            ...) {
   insight::check_if_installed("BayesFactor")
 
@@ -83,6 +84,12 @@ model_parameters.BFBayesFactor <- function(model,
     return(NULL)
   }
 
+  ## TODO: remove deprecation warning later
+  if (!is.null(effectsize_type)) {
+    insight::format_warning("Argument `effectsize_type` is deprecated. Use `es_type` instead.")
+    es_type <- effectsize_type
+  }
+
   out <- bayestestR::describe_posterior(
     model,
     centrality = centrality,
@@ -132,7 +139,7 @@ model_parameters.BFBayesFactor <- function(model,
   }
 
   # Effect size?
-  if (!is.null(effectsize_type)) {
+  if (!is.null(es_type)) {
     # needs {effectsize} to be installed
     insight::check_if_installed("effectsize")
 
@@ -144,7 +151,7 @@ model_parameters.BFBayesFactor <- function(model,
           dispersion = dispersion,
           ci_method = ci_method,
           rope_ci = rope_ci,
-          type = effectsize_type,
+          type = es_type,
           ...
         )
 
diff --git a/R/methods_aov.R b/R/methods_aov.R
index a021114d9..50c09e33f 100644
--- a/R/methods_aov.R
+++ b/R/methods_aov.R
@@ -7,7 +7,7 @@
 #' @param model Object of class [aov()], [anova()],
 #'   `aovlist`, `Gam`, [manova()], `Anova.mlm`,
 #'   `afex_aov` or `maov`.
-#' @param effectsize_type The effect size of interest. Not that possibly not all
+#' @param es_type The effect size of interest. Not that possibly not all
 #'   effect sizes are applicable to the model object. See 'Details'. For Anova
 #'   models, can also be a character vector with multiple effect size names.
 #' @param df_error Denominator degrees of freedom (or degrees of freedom of the
@@ -18,7 +18,7 @@
 #'   ANOVA-tables using `car::Anova()` will be returned. (Ignored for
 #'   `afex_aov`.)
 #' @param ci Confidence Interval (CI) level for effect sizes specified in
-#'   `effectsize_type`. The default, `NULL`, will compute no confidence
+#'   `es_type`. The default, `NULL`, will compute no confidence
 #'   intervals. `ci` should be a scalar between 0 and 1.
 #' @param test String, indicating the type of test for `Anova.mlm` to be
 #'   returned. If `"multivariate"` (or `NULL`), returns the summary of
@@ -35,6 +35,7 @@
 #'   (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 effectsize_type Deprecated. Use `es_type` instead.
 #' @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
@@ -65,13 +66,13 @@
 #' model <- aov(Sepal.Length ~ Sepal.Big, data = df)
 #' model_parameters(model)
 #'
-#' model_parameters(model, effectsize_type = c("omega", "eta"), ci = 0.9)
+#' model_parameters(model, es_type = c("omega", "eta"), ci = 0.9)
 #'
 #' model <- anova(lm(Sepal.Length ~ Sepal.Big, data = df))
 #' model_parameters(model)
 #' model_parameters(
 #'   model,
-#'   effectsize_type = c("omega", "eta", "epsilon"),
+#'   es_type = c("omega", "eta", "epsilon"),
 #'   alternative = "greater"
 #' )
 #'
@@ -91,7 +92,7 @@
 #' # parameters table including effect sizes
 #' model_parameters(
 #'   model,
-#'   effectsize_type = "eta",
+#'   es_type = "eta",
 #'   ci = 0.9,
 #'   df_error = dof_satterthwaite(mm)[2:3]
 #' )
@@ -104,16 +105,23 @@ model_parameters.aov <- function(model,
                                  alternative = NULL,
                                  test = NULL,
                                  power = FALSE,
-                                 effectsize_type = NULL,
+                                 es_type = NULL,
                                  keep = NULL,
                                  drop = NULL,
                                  table_wide = FALSE,
                                  verbose = TRUE,
+                                 effectsize_type = NULL,
                                  ...) {
   # save model object, for later checks
   original_model <- model
   object_name <- insight::safe_deparse_symbol(substitute(model))
 
+  ## TODO: remove deprecation warning later
+  if (!is.null(effectsize_type)) {
+    insight::format_warning("Argument `effectsize_type` is deprecated. Use `es_type` instead.")
+    es_type <- effectsize_type
+  }
+
   if (inherits(model, "aov") && !is.null(type) && type > 1) {
     if (requireNamespace("car", quietly = TRUE)) {
       model <- car::Anova(model, type = type)
@@ -144,7 +152,7 @@ model_parameters.aov <- function(model,
   params <- .effectsizes_for_aov(
     model,
     params = params,
-    effectsize_type = effectsize_type,
+    es_type = es_type,
     df_error = df_error,
     ci = ci,
     alternative = alternative,
@@ -250,7 +258,7 @@ model_parameters.aovlist <- model_parameters.aov
 #' @rdname model_parameters.aov
 #' @export
 model_parameters.afex_aov <- function(model,
-                                      effectsize_type = NULL,
+                                      es_type = NULL,
                                       df_error = NULL,
                                       type = NULL,
                                       keep = NULL,
@@ -270,7 +278,7 @@ model_parameters.afex_aov <- function(model,
   out <- .effectsizes_for_aov(
     model,
     params = out,
-    effectsize_type = effectsize_type,
+    es_type = es_type,
     df_error = df_error,
     verbose = verbose,
     ...
@@ -432,19 +440,19 @@ model_parameters.maov <- model_parameters.aov
 
 .effectsizes_for_aov <- function(model,
                                  params,
-                                 effectsize_type = NULL,
+                                 es_type = NULL,
                                  df_error = NULL,
                                  ci = NULL,
                                  alternative = NULL,
                                  verbose = TRUE,
                                  ...) {
   # user actually does not want to compute effect sizes
-  if (is.null(effectsize_type)) {
+  if (is.null(es_type)) {
     return(params)
   }
 
   # is valid effect size?
-  if (!all(effectsize_type %in% c("eta", "omega", "epsilon", "f", "f2"))) {
+  if (!all(es_type %in% c("eta", "omega", "epsilon", "f", "f2"))) {
     return(params)
   }
 
@@ -462,7 +470,7 @@ model_parameters.maov <- model_parameters.aov
   }
 
   # multiple effect sizes possible
-  for (es in effectsize_type) {
+  for (es in es_type) {
     fx <- effectsize::effectsize(
       model,
       type = es,
diff --git a/R/methods_htest.R b/R/methods_htest.R
index 4586a6cf7..4e070c61d 100644
--- a/R/methods_htest.R
+++ b/R/methods_htest.R
@@ -16,13 +16,13 @@
 #' model_parameters(model)
 #'
 #' model <- t.test(iris$Sepal.Width, iris$Sepal.Length)
-#' model_parameters(model, effectsize_type = "hedges_g")
+#' model_parameters(model, es_type = "hedges_g")
 #'
 #' model <- t.test(mtcars$mpg ~ mtcars$vs)
-#' model_parameters(model, effectsize_type = "hedges_g")
+#' model_parameters(model, es_type = "hedges_g")
 #'
 #' model <- t.test(iris$Sepal.Width, mu = 1)
-#' model_parameters(model, effectsize_type = "cohens_d")
+#' model_parameters(model, es_type = "cohens_d")
 #'
 #' data(airquality)
 #' airquality$Month <- factor(airquality$Month, labels = month.abb[5:9])
@@ -35,7 +35,7 @@
 #' model_parameters(model)
 #'
 #' model <- suppressWarnings(chisq.test(table(mtcars$am, mtcars$cyl)))
-#' model_parameters(model, effectsize_type = "cramers_v")
+#' model_parameters(model, es_type = "cramers_v")
 #'
 #' @return A data frame of indices related to the model's parameters.
 #'
@@ -44,15 +44,22 @@ model_parameters.htest <- function(model,
                                    ci = 0.95,
                                    alternative = NULL,
                                    bootstrap = FALSE,
-                                   effectsize_type = NULL,
+                                   es_type = NULL,
                                    verbose = TRUE,
+                                   effectsize_type = NULL,
                                    ...) {
+  ## TODO: remove deprecation warning later
+  if (!is.null(effectsize_type)) {
+    insight::format_warning("Argument `effectsize_type` is deprecated. Use `es_type` instead.")
+    es_type <- effectsize_type
+  }
+
   if (bootstrap) {
     insight::format_error("Bootstrapped h-tests are not yet implemented.")
   } else {
     parameters <- .extract_parameters_htest(
       model,
-      effectsize_type = effectsize_type,
+      es_type = es_type,
       ci = ci,
       alternative = alternative,
       verbose = verbose,
@@ -121,7 +128,7 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
 
 #' @keywords internal
 .extract_parameters_htest <- function(model,
-                                      effectsize_type = NULL,
+                                      es_type = NULL,
                                       ci = 0.95,
                                       alternative = NULL,
                                       verbose = TRUE,
@@ -164,7 +171,7 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
 
   out <- .add_effectsize_htest(model,
     out,
-    effectsize_type = effectsize_type,
+    es_type = es_type,
     ci = ci,
     alternative = alternative,
     verbose = verbose,
@@ -568,20 +575,20 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
 
 .add_effectsize_htest <- function(model,
                                   out,
-                                  effectsize_type = NULL,
+                                  es_type = NULL,
                                   ci = 0.95,
                                   alternative = NULL,
                                   verbose = TRUE,
                                   ...) {
   # check if effect sizes are requested
-  if (!requireNamespace("effectsize", quietly = TRUE) || is.null(effectsize_type)) {
+  if (!requireNamespace("effectsize", quietly = TRUE) || is.null(es_type)) {
     return(out)
   }
 
   # return on invalid options. We may have partial matching with argument
-  # `effects` for `effectsize_type`, and thus all "effects" options should be
+  # `effects` for `es_type`, and thus all "effects" options should be
   # ignored.
-  if (effectsize_type %in% c("fixed", "random", "all")) {
+  if (es_type %in% c("fixed", "random", "all")) {
     return(out)
   }
 
@@ -590,7 +597,7 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
     {
       effectsize::effectsize(
         model,
-        type = effectsize_type,
+        type = es_type,
         ci = ci,
         alternative = alternative,
         verbose = verbose,
@@ -600,7 +607,7 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
     error = function(e) {
       if (verbose) {
         msg <- c(
-          paste0("Could not compute effectsize ", effectsize::get_effectsize_label(effectsize_type), "."),
+          paste0("Could not compute effectsize ", effectsize::get_effectsize_label(es_type), "."),
           paste0("Possible reason: ", e$message)
         )
         insight::format_alert(msg)
@@ -616,7 +623,7 @@ model_parameters.svytable <- function(model, verbose = TRUE, ...) {
   ## TODO: check if effectsize prefixes are correct @mattansb
 
   # Find prefix for CI-columns
-  prefix <- switch(effectsize_type,
+  prefix <- switch(es_type,
     cohens_g = "Cohens_",
     cramers_v = "Cramers_",
     phi = "phi_",
diff --git a/R/methods_other.R b/R/methods_other.R
index f1afb42e1..f5110bf59 100644
--- a/R/methods_other.R
+++ b/R/methods_other.R
@@ -36,15 +36,22 @@ degrees_of_freedom.complmrob <- function(model, method = "wald", ...) {
 #' @inheritParams model_parameters.aov
 #' @export
 model_parameters.Gam <- function(model,
-                                 effectsize_type = NULL,
+                                 es_type = NULL,
                                  df_error = NULL,
                                  type = NULL,
                                  table_wide = FALSE,
                                  verbose = TRUE,
+                                 effectsize_type = NULL,
                                  ...) {
+  ## TODO: remove deprecation warning later
+  if (!is.null(effectsize_type)) {
+    insight::format_warning("Argument `effectsize_type` is deprecated. Use `es_type` instead.")
+    es_type <- effectsize_type
+  }
+
   model_parameters(
     summary(model)$parametric.anova,
-    effectsize_type = effectsize_type,
+    es_type = es_type,
     df_error = df_error,
     type = type,
     table_wide = table_wide,
diff --git a/man/model_parameters.BFBayesFactor.Rd b/man/model_parameters.BFBayesFactor.Rd
index b24faeaa8..b88312181 100644
--- a/man/model_parameters.BFBayesFactor.Rd
+++ b/man/model_parameters.BFBayesFactor.Rd
@@ -14,9 +14,10 @@
   rope_range = "default",
   rope_ci = 0.95,
   priors = TRUE,
-  effectsize_type = NULL,
+  es_type = NULL,
   include_proportions = FALSE,
   verbose = TRUE,
+  effectsize_type = NULL,
   ...
 )
 }
@@ -58,7 +59,7 @@ proportion of HDI, to use for the percentage in ROPE.}
 
 \item{priors}{Add the prior used for each parameter.}
 
-\item{effectsize_type}{The effect size of interest. Not that possibly not all
+\item{es_type}{The effect size of interest. Not that possibly not all
 effect sizes are applicable to the model object. See 'Details'. For Anova
 models, can also be a character vector with multiple effect size names.}
 
@@ -69,6 +70,8 @@ information is often redundant.}
 
 \item{verbose}{Toggle off warnings.}
 
+\item{effectsize_type}{Deprecated. Use \code{es_type} instead.}
+
 \item{...}{Additional arguments to be passed to or from methods.}
 }
 \value{
@@ -98,7 +101,7 @@ the \emph{g} parameters; See the \emph{Bayes Factors for ANOVAs} paper
 # Bayesian t-test
 model <- BayesFactor::ttestBF(x = rnorm(100, 1, 1))
 model_parameters(model)
-model_parameters(model, effectsize_type = "cohens_d", ci = 0.9)
+model_parameters(model, es_type = "cohens_d", ci = 0.9)
 
 # Bayesian contingency table analysis
 data(raceDolls)
@@ -111,7 +114,7 @@ model_parameters(bf,
   centrality = "mean",
   dispersion = TRUE,
   verbose = FALSE,
-  effectsize_type = "cramers_v"
+  es_type = "cramers_v"
 )
 }
 \dontshow{\}) # examplesIf}
diff --git a/man/model_parameters.aov.Rd b/man/model_parameters.aov.Rd
index 16f1d249e..4033ecc41 100644
--- a/man/model_parameters.aov.Rd
+++ b/man/model_parameters.aov.Rd
@@ -13,17 +13,18 @@
   alternative = NULL,
   test = NULL,
   power = FALSE,
-  effectsize_type = NULL,
+  es_type = NULL,
   keep = NULL,
   drop = NULL,
   table_wide = FALSE,
   verbose = TRUE,
+  effectsize_type = NULL,
   ...
 )
 
 \method{model_parameters}{afex_aov}(
   model,
-  effectsize_type = NULL,
+  es_type = NULL,
   df_error = NULL,
   type = NULL,
   keep = NULL,
@@ -47,7 +48,7 @@ for ANOVA-tables from mixed models. See 'Examples'. (Ignored for
 \code{afex_aov}.)}
 
 \item{ci}{Confidence Interval (CI) level for effect sizes specified in
-\code{effectsize_type}. The default, \code{NULL}, will compute no confidence
+\code{es_type}. The default, \code{NULL}, will compute no confidence
 intervals. \code{ci} should be a scalar between 0 and 1.}
 
 \item{alternative}{A character string specifying the alternative hypothesis;
@@ -64,7 +65,7 @@ the multivariate test (that is also given by the \code{print}-method). If
 \item{power}{Logical, if \code{TRUE}, adds a column with power for each
 parameter.}
 
-\item{effectsize_type}{The effect size of interest. Not that possibly not all
+\item{es_type}{The effect size of interest. Not that possibly not all
 effect sizes are applicable to the model object. See 'Details'. For Anova
 models, can also be a character vector with multiple effect size names.}
 
@@ -96,6 +97,8 @@ be in the same row. Default: \code{FALSE}.}
 
 \item{verbose}{Toggle warnings and messages.}
 
+\item{effectsize_type}{Deprecated. Use \code{es_type} instead.}
+
 \item{...}{Arguments passed to \code{\link[effectsize:effectsize]{effectsize::effectsize()}}. For example,
 to calculate \emph{partial} effect sizes types, use \code{partial = TRUE}. For objects
 of class \code{htest} or \code{BFBayesFactor}, \code{adjust = TRUE} can be used to return
@@ -161,13 +164,13 @@ df$Sepal.Big <- ifelse(df$Sepal.Width >= 3, "Yes", "No")
 model <- aov(Sepal.Length ~ Sepal.Big, data = df)
 model_parameters(model)
 
-model_parameters(model, effectsize_type = c("omega", "eta"), ci = 0.9)
+model_parameters(model, es_type = c("omega", "eta"), ci = 0.9)
 
 model <- anova(lm(Sepal.Length ~ Sepal.Big, data = df))
 model_parameters(model)
 model_parameters(
   model,
-  effectsize_type = c("omega", "eta", "epsilon"),
+  es_type = c("omega", "eta", "epsilon"),
   alternative = "greater"
 )
 
@@ -187,7 +190,7 @@ model_parameters(model)
 # parameters table including effect sizes
 model_parameters(
   model,
-  effectsize_type = "eta",
+  es_type = "eta",
   ci = 0.9,
   df_error = dof_satterthwaite(mm)[2:3]
 )
diff --git a/man/model_parameters.cgam.Rd b/man/model_parameters.cgam.Rd
index 90a5ff164..7b684a368 100644
--- a/man/model_parameters.cgam.Rd
+++ b/man/model_parameters.cgam.Rd
@@ -34,11 +34,12 @@
 
 \method{model_parameters}{Gam}(
   model,
-  effectsize_type = NULL,
+  es_type = NULL,
   df_error = NULL,
   type = NULL,
   table_wide = FALSE,
   verbose = TRUE,
+  effectsize_type = NULL,
   ...
 )
 
@@ -143,7 +144,7 @@ names.}
 \code{bootstrap = TRUE}, arguments like \code{type} or \code{parallel} are
 passed down to \code{bootstrap_model()}.}
 
-\item{effectsize_type}{The effect size of interest. Not that possibly not all
+\item{es_type}{The effect size of interest. Not that possibly not all
 effect sizes are applicable to the model object. See 'Details'. For Anova
 models, can also be a character vector with multiple effect size names.}
 
@@ -159,6 +160,8 @@ ANOVA-tables using \code{car::Anova()} will be returned. (Ignored for
 \item{table_wide}{Logical that decides whether the ANOVA table should be in
 wide format, i.e. should the numerator and denominator degrees of freedom
 be in the same row. Default: \code{FALSE}.}
+
+\item{effectsize_type}{Deprecated. Use \code{es_type} instead.}
 }
 \value{
 A data frame of indices related to the model's parameters.
diff --git a/man/model_parameters.htest.Rd b/man/model_parameters.htest.Rd
index dcd667b86..c988acf4d 100644
--- a/man/model_parameters.htest.Rd
+++ b/man/model_parameters.htest.Rd
@@ -10,8 +10,9 @@
   ci = 0.95,
   alternative = NULL,
   bootstrap = FALSE,
-  effectsize_type = NULL,
+  es_type = NULL,
   verbose = TRUE,
+  effectsize_type = NULL,
   ...
 )
 
@@ -39,12 +40,14 @@ the \href{https://easystats.github.io/effectsize/}{effectsize_CIs vignette}.}
 
 \item{bootstrap}{Should estimates be bootstrapped?}
 
-\item{effectsize_type}{The effect size of interest. Not that possibly not all
+\item{es_type}{The effect size of interest. Not that possibly not all
 effect sizes are applicable to the model object. See 'Details'. For Anova
 models, can also be a character vector with multiple effect size names.}
 
 \item{verbose}{Toggle warnings and messages.}
 
+\item{effectsize_type}{Deprecated. Use \code{es_type} instead.}
+
 \item{...}{Arguments passed to or from other methods. For instance, when
 \code{bootstrap = TRUE}, arguments like \code{type} or \code{parallel} are
 passed down to \code{bootstrap_model()}.}
@@ -124,13 +127,13 @@ model <- cor.test(mtcars$mpg, mtcars$cyl, method = "pearson")
 model_parameters(model)
 
 model <- t.test(iris$Sepal.Width, iris$Sepal.Length)
-model_parameters(model, effectsize_type = "hedges_g")
+model_parameters(model, es_type = "hedges_g")
 
 model <- t.test(mtcars$mpg ~ mtcars$vs)
-model_parameters(model, effectsize_type = "hedges_g")
+model_parameters(model, es_type = "hedges_g")
 
 model <- t.test(iris$Sepal.Width, mu = 1)
-model_parameters(model, effectsize_type = "cohens_d")
+model_parameters(model, es_type = "cohens_d")
 
 data(airquality)
 airquality$Month <- factor(airquality$Month, labels = month.abb[5:9])
@@ -143,6 +146,6 @@ model <- suppressWarnings(pairwise.prop.test(smokers, patients))
 model_parameters(model)
 
 model <- suppressWarnings(chisq.test(table(mtcars$am, mtcars$cyl)))
-model_parameters(model, effectsize_type = "cramers_v")
+model_parameters(model, es_type = "cramers_v")
 
 }
diff --git a/tests/testthat/test-model_parameters.BFBayesFactor.R b/tests/testthat/test-model_parameters.BFBayesFactor.R
index 6acabdb50..14dfb8474 100644
--- a/tests/testthat/test-model_parameters.BFBayesFactor.R
+++ b/tests/testthat/test-model_parameters.BFBayesFactor.R
@@ -84,7 +84,7 @@ test_that("model_parameters.BFBayesFactor", {
     centrality = "mean",
     dispersion = TRUE,
     verbose = FALSE,
-    effectsize_type = "cramers_v",
+    es_type = "cramers_v",
     adjust = TRUE,
     include_proportions = TRUE
   ))
@@ -158,7 +158,7 @@ test_that("model_parameters.BFBayesFactor, with effectsize", {
   skip_if_not_installed("BayesFactor")
   set.seed(123)
   df_t_es <- as.data.frame(
-    parameters(BayesFactor::ttestBF(mtcars$wt, mu = 3), effectsize_type = "cohens_d")
+    parameters(BayesFactor::ttestBF(mtcars$wt, mu = 3), es_type = "cohens_d")
   )
 
   # TODO: fix column order
diff --git a/tests/testthat/test-model_parameters.anova.R b/tests/testthat/test-model_parameters.anova.R
index 9533031d4..3095a9057 100644
--- a/tests/testthat/test-model_parameters.anova.R
+++ b/tests/testthat/test-model_parameters.anova.R
@@ -94,7 +94,7 @@ test_that("model_parameters_Anova-effectsize", {
   # parameters table including effect sizes
   mp <- model_parameters(
     model,
-    effectsize_type = "eta",
+    es_type = "eta",
     ci = 0.9,
     df_error = dof_satterthwaite(mm)[2:3]
   )
diff --git a/tests/testthat/test-model_parameters.aov.R b/tests/testthat/test-model_parameters.aov.R
index 09e40803a..a1d069107 100644
--- a/tests/testthat/test-model_parameters.aov.R
+++ b/tests/testthat/test-model_parameters.aov.R
@@ -8,7 +8,7 @@ iris$Cat2 <- rep(c("A", "B"), length.out = nrow(iris))
 test_that("model_parameters.aov", {
   skip_if_not_installed("effectsize", minimum_version = "0.5.0")
   model <- aov(Sepal.Width ~ Species, data = iris)
-  mp <- suppressMessages(model_parameters(model, effectsize_type = c("omega", "eta", "epsilon")))
+  mp <- suppressMessages(model_parameters(model, es_type = c("omega", "eta", "epsilon")))
   expect_identical(mp$Parameter, c("Species", "Residuals"))
   expect_equal(mp$Sum_Squares, c(11.34493, 16.962), tolerance = 1e-3)
 })
@@ -16,7 +16,7 @@ test_that("model_parameters.aov", {
 test_that("model_parameters.aov", {
   skip_if_not_installed("effectsize", minimum_version = "0.5.0")
   model <- aov(Sepal.Width ~ Species, data = iris)
-  mp <- suppressMessages(model_parameters(model, effectsize_type = c("omega", "eta", "epsilon")))
+  mp <- suppressMessages(model_parameters(model, es_type = c("omega", "eta", "epsilon")))
   expect_identical(sum(mp$df), 149)
   expect_named(mp, c(
     "Parameter", "Sum_Squares", "df", "Mean_Square", "F", "p",
@@ -24,7 +24,7 @@ test_that("model_parameters.aov", {
   ))
 
   model <- aov(Sepal.Length ~ Species * Cat1 * Cat2, data = iris)
-  expect_identical(sum(model_parameters(model, effectsize_type = c("omega", "eta", "epsilon"), verbose = FALSE)$df), 149)
+  expect_identical(sum(model_parameters(model, es_type = c("omega", "eta", "epsilon"), verbose = FALSE)$df), 149)
 
   model <- aov(Sepal.Length ~ Species / Cat1 * Cat2, data = iris)
   expect_identical(sum(model_parameters(model, verbose = FALSE)$df), 149)
diff --git a/tests/testthat/test-model_parameters.aov_es_ci.R b/tests/testthat/test-model_parameters.aov_es_ci.R
index 826f895f2..4e5a5f969 100644
--- a/tests/testthat/test-model_parameters.aov_es_ci.R
+++ b/tests/testthat/test-model_parameters.aov_es_ci.R
@@ -9,7 +9,7 @@ test_that("model_parameters.aov", {
   model <- aov(Sepal.Width ~ Species, data = iris)
   mp <- suppressMessages(model_parameters(
     model,
-    effectsize_type = c("omega", "eta", "epsilon"),
+    es_type = c("omega", "eta", "epsilon"),
     ci = 0.9,
     alternative = "greater"
   ))
@@ -28,7 +28,7 @@ test_that("model_parameters.aov", {
   ))
 
   model <- aov(Sepal.Length ~ Species * Cat1 * Cat2, data = iris)
-  mp <- model_parameters(model, effectsize_type = "eta", ci = 0.9, partial = FALSE, alternative = "greater")
+  mp <- model_parameters(model, es_type = "eta", ci = 0.9, partial = FALSE, alternative = "greater")
   es <- effectsize::eta_squared(model, partial = FALSE, ci = 0.9)
   expect_equal(na.omit(mp$Eta2_CI_low), es$CI_low, tolerance = 1e-3, ignore_attr = TRUE)
   expect_equal(mp$Eta2_CI_low, c(0.5572, 0, 0, 0, 0, 0, 0, NA), tolerance = 1e-3, ignore_attr = TRUE)
@@ -53,7 +53,7 @@ test_that("model_parameters.anova", {
   model <- anova(lm(Sepal.Length ~ Species * Cat1 * Cat2, data = iris))
   mp <- model_parameters(
     model,
-    effectsize_type = c("omega", "eta", "epsilon"),
+    es_type = c("omega", "eta", "epsilon"),
     partial = TRUE,
     ci = 0.9,
     alternative = "greater"
@@ -75,7 +75,7 @@ test_that("model_parameters.anova", {
   skip_if_not_installed("effectsize", minimum_version = "0.5.1")
   model <- aov(wt ~ cyl + Error(gear), data = mtcars)
   suppressWarnings({
-    mp <- model_parameters(model, effectsize_type = c("omega", "eta", "epsilon"), partial = TRUE, ci = 0.9)
+    mp <- model_parameters(model, es_type = c("omega", "eta", "epsilon"), partial = TRUE, ci = 0.9)
     es <- effectsize::omega_squared(model, partial = TRUE, ci = 0.9, verbose = FALSE)
   })
   expect_equal(na.omit(mp$Omega2_CI_low), es$CI_low[2], tolerance = 1e-3, ignore_attr = TRUE)
@@ -107,7 +107,7 @@ test_that("model_parameters.car-anova", {
       contrasts = list(fcategory = contr.sum, partner.status = contr.sum)
     ))
 
-  mp <- model_parameters(model, effectsize_type = c("omega", "eta", "epsilon"), partial = TRUE, ci = 0.9)
+  mp <- model_parameters(model, es_type = c("omega", "eta", "epsilon"), partial = TRUE, ci = 0.9)
   es <- effectsize::omega_squared(model, partial = TRUE, ci = 0.9)
   expect_equal(na.omit(mp$Omega2_CI_low), es$CI_low, tolerance = 1e-3, ignore_attr = TRUE)
   expect_equal(mp$Omega2_CI_low, c(0, 0.05110, 0.00666, NA), tolerance = 1e-3, ignore_attr = TRUE)
@@ -133,7 +133,7 @@ test_that("model_parameters.maov", {
 
   mp <- suppressMessages(model_parameters(
     model,
-    effectsize_type = c("omega", "eta", "epsilon"),
+    es_type = c("omega", "eta", "epsilon"),
     partial = TRUE,
     ci = 0.9
   ))
@@ -165,7 +165,7 @@ test_that("works with aov", {
   df_aov <-
     as.data.frame(parameters::model_parameters(npk.aov,
       ci = 0.95,
-      effectsize_type = c("eta", "omega"),
+      es_type = c("eta", "omega"),
       partial = FALSE
     ))
 
@@ -280,7 +280,7 @@ test_that("works with manova", {
   df_manova <-
     as.data.frame(model_parameters(m,
       ci = 0.99,
-      effectsize_type = c("epsilon", "omega"),
+      es_type = c("epsilon", "omega"),
       partial = TRUE
     ))
 
@@ -333,7 +333,7 @@ test_that("works with Gam", {
   df_Gam <-
     as.data.frame(model_parameters(g,
       ci = 0.50,
-      effectsize_type = "omega",
+      es_type = "omega",
       partial = TRUE
     ))
 
@@ -384,7 +384,7 @@ test_that("works with anova", {
   df_car <-
     as.data.frame(model_parameters(mod,
       ci = 0.89,
-      effectsize_type = c("eta", "epsilon"),
+      es_type = c("eta", "epsilon"),
       partial = FALSE
     ))
 
diff --git a/tests/testthat/test-model_parameters.htest.R b/tests/testthat/test-model_parameters.htest.R
index 15a76c6f4..dad34b4b5 100644
--- a/tests/testthat/test-model_parameters.htest.R
+++ b/tests/testthat/test-model_parameters.htest.R
@@ -68,14 +68,14 @@ test_that("model_parameters-chisq-test works with `svychisq` objects", {
 
 test_that("model_parameters-chisq-test adjusted", {
   expect_message({
-    mp <- model_parameters(stats::chisq.test(table(mtcars$am)), effectsize_type = "phi", ci = 0.95)
+    mp <- model_parameters(stats::chisq.test(table(mtcars$am)), es_type = "phi", ci = 0.95)
   })
   expect_equal(mp$Chi2, 1.125, tolerance = 1e-3)
   expect_named(mp, c("Chi2", "df", "p", "Method"))
 })
 
 test_that("model_parameters-t-test standardized d", {
-  params <- model_parameters(t.test(iris$Sepal.Width, iris$Sepal.Length), effectsize_type = "cohens_d")
+  params <- model_parameters(t.test(iris$Sepal.Width, iris$Sepal.Length), es_type = "cohens_d")
   expect_equal(params$Cohens_d, -4.210417, tolerance = 0.05)
   expect_equal(params$d_CI_low, -4.655306, tolerance = 0.05)
   expect_named(
@@ -89,7 +89,7 @@ test_that("model_parameters-t-test standardized d", {
 })
 
 test_that("model_parameters-t-test standardized d", {
-  mp <- model_parameters(t.test(mtcars$mpg ~ mtcars$vs), effectsize_type = "cohens_d", verbose = FALSE)
+  mp <- model_parameters(t.test(mtcars$mpg ~ mtcars$vs), es_type = "cohens_d", verbose = FALSE)
   expect_equal(mp$Cohens_d, -1.696032, tolerance = 1e-3)
   expect_named(
     mp,
diff --git a/vignettes/model_parameters.Rmd b/vignettes/model_parameters.Rmd
index 719ffb69c..709a5ec0d 100644
--- a/vignettes/model_parameters.Rmd
+++ b/vignettes/model_parameters.Rmd
@@ -106,7 +106,7 @@ summaries, including confidence intervals
 
 ```{r eval=successfully_loaded["effectsize"]}
 aov(Sepal.Length ~ Species, data = iris) |>
-  parameters(effectsize_type = c("omega", "eta", "epsilon"))
+  parameters(es_type = c("omega", "eta", "epsilon"))
 ```
 
 Let's complicate things further with an interaction term:
@@ -114,7 +114,7 @@ Let's complicate things further with an interaction term:
 ```{r eval=successfully_loaded["effectsize"]}
 aov(Sepal.Length ~ Species * Sepal.Width, data = iris) |>
   parameters(
-    effectsize_type = c("omega", "eta"),
+    es_type = c("omega", "eta"),
     ci = 0.8
   )
 ```