diff --git a/DESCRIPTION b/DESCRIPTION
index 85f666826..184e71ddc 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: performance
 Title: Assessment of Regression Models Performance
-Version: 0.15.3.6
+Version: 0.15.3.7
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
diff --git a/NEWS.md b/NEWS.md
index 664270df7..8f400845b 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -6,6 +6,9 @@
   `RMSR` (Root Mean Square Residual) instead of `RMSA`. The `RMSR_corrected`
   column (previously `RMSA_corrected`) is also renamed accordingly.
 
+* The first argument in `check_model()`, `check_predictions()` and
+  `check_convergence()` was renamed to `model`.
+
 ## Changes
 
 * `check_model()` now limits the number of data points for models with many
@@ -13,7 +16,7 @@
   argument.
 
 * `check_model()` can now show or hide confidence intervals using the `show_ci`
-  argument. For models with only categorical predictors, cnmfidence intervals
+  argument. For models with only categorical predictors, confidence intervals
   are not shown by default.
 
 ## Bug fixes
diff --git a/R/check_convergence.R b/R/check_convergence.R
index fa05a4623..b196c0753 100644
--- a/R/check_convergence.R
+++ b/R/check_convergence.R
@@ -4,9 +4,10 @@
 #' @description `check_convergence()` provides an alternative convergence
 #'   test for `merMod`-objects.
 #'
-#' @param x A `merMod` or `glmmTMB`-object.
+#' @param model A `merMod` or `glmmTMB`-object.
 #' @param tolerance Indicates up to which value the convergence result is
 #'   accepted. The smaller `tolerance` is, the stricter the test will be.
+#' @param x Deprecated, please use `model` instead.
 #' @param ... Currently not used.
 #'
 #' @return `TRUE` if convergence is fine and `FALSE` if convergence
@@ -50,8 +51,16 @@
 #' check_convergence(model)
 #' }
 #' @export
-check_convergence <- function(x, tolerance = 0.001, ...) {
-  out <- .safe(insight::is_converged(x, tolerance = tolerance, ...))
+check_convergence <- function(model = NULL, tolerance = 0.001, x = NULL, ...) {
+  ## TODO remove deprecation warning later
+  if (!is.null(x) && is.null(model)) {
+    insight::format_warning(
+      "Argument `x` is deprecated; please use `model` instead."
+    )
+    model <- x
+  }
+  .is_model_valid(model)
+  out <- .safe(insight::is_converged(model, tolerance = tolerance, ...))
   if (is.null(out)) {
     insight::format_alert("Could not compute convergence information.")
     out <- NA
diff --git a/R/check_model.R b/R/check_model.R
index ddccebe23..5ff13b21a 100644
--- a/R/check_model.R
+++ b/R/check_model.R
@@ -9,7 +9,7 @@
 #' If `check_model()` doesn't work as expected, try setting `verbose = TRUE` to
 #' get hints about possible problems.
 #'
-#' @param x A model object.
+#' @param model A model object.
 #' @param size_dot,size_line Size of line and dot-geoms.
 #' @param base_size,size_title,size_axis_title Base font size for axis and plot titles.
 #' @param panel Logical, if `TRUE`, plots are arranged as panels; else,
@@ -56,6 +56,8 @@
 #' @param verbose If `FALSE` (default), suppress most warning messages.
 #' @param ... Arguments passed down to the individual check functions, especially
 #' to `check_predictions()` and `binned_residuals()`.
+#' @param x Deprecated, please use `model` instead.
+#'
 #' @inheritParams check_predictions
 #'
 #' @return The data frame that is used for plotting.
@@ -191,7 +193,7 @@
 #' check_model(m, panel = FALSE)
 #' }
 #' @export
-check_model <- function(x, ...) {
+check_model <- function(model = NULL, ...) {
   UseMethod("check_model")
 }
 
@@ -201,7 +203,7 @@ check_model <- function(x, ...) {
 #' @rdname check_model
 #' @export
 check_model.default <- function(
-  x,
+  model = NULL,
   panel = TRUE,
   check = "all",
   detrend = TRUE,
@@ -221,14 +223,23 @@ check_model.default <- function(
   colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
   theme = see::theme_lucid(),
   verbose = FALSE,
+  x = NULL,
   ...
 ) {
+  ## TODO remove deprecation warning later
+  if (!is.null(x) && is.null(model)) {
+    insight::format_warning(
+      "Argument `x` is deprecated; please use `model` instead."
+    )
+    model <- x
+  }
+
   # check model formula
   if (verbose) {
-    insight::formula_ok(x)
+    insight::formula_ok(model)
   }
 
-  minfo <- insight::model_info(x, verbose = FALSE)
+  minfo <- insight::model_info(model, verbose = FALSE)
 
   # set default for residual_type
   if (is.null(residual_type)) {
@@ -250,10 +261,10 @@ check_model.default <- function(
 
   assumptions_data <- tryCatch(
     if (minfo$is_bayesian) {
-      suppressWarnings(.check_assumptions_stan(x, ...))
+      suppressWarnings(.check_assumptions_stan(model, ...))
     } else if (minfo$is_linear) {
       suppressWarnings(.check_assumptions_linear(
-        x,
+        model,
         minfo,
         check,
         residual_type,
@@ -262,7 +273,7 @@ check_model.default <- function(
       ))
     } else {
       suppressWarnings(.check_assumptions_glm(
-        x,
+        model,
         minfo,
         check,
         residual_type,
@@ -283,7 +294,7 @@ check_model.default <- function(
       paste("`check_model()` returned following error:", cleaned_string),
       paste0(
         "\nIf the error message does not help identifying your problem, another reason why `check_model()` failed might be that models of class `",
-        class(x)[1],
+        class(model)[1],
         "` are not yet supported."
       ) # nolint
     )
@@ -293,7 +304,7 @@ check_model.default <- function(
   if (is.null(assumptions_data$QQ) && residual_type == "simulated") {
     insight::format_alert(paste0(
       "Cannot simulate residuals for models of class `",
-      class(x)[1],
+      class(model)[1],
       "`. Please try `check_model(..., residual_type = \"normal\")` instead."
     ))
   }
@@ -309,7 +320,7 @@ check_model.default <- function(
   }
 
   # set default for show_dots, based on "model size"
-  n <- .safe(insight::n_obs(x))
+  n <- .safe(insight::n_obs(model))
   if (is.null(show_dots)) {
     show_dots <- is.null(n) || n <= 1e5
   }
@@ -322,7 +333,7 @@ check_model.default <- function(
   }
 
   # if we have only categorical predictors, we don't show CI by default
-  parameter_types <- .safe(parameters::parameters_type(x))
+  parameter_types <- .safe(parameters::parameters_type(model))
   if (
     !is.null(parameter_types) && all(parameter_types$Type %in% c("intercept", "factor"))
   ) {
@@ -350,7 +361,7 @@ check_model.default <- function(
   attr(assumptions_data, "bandwidth") <- bandwidth
   attr(assumptions_data, "type") <- type
   attr(assumptions_data, "maximum_dots") <- maximum_dots
-  attr(assumptions_data, "model_class") <- class(x)[1]
+  attr(assumptions_data, "model_class") <- class(model)[1]
   assumptions_data
 }
 
@@ -377,7 +388,7 @@ plot.check_model <- function(x, ...) {
 
 #' @export
 check_model.stanreg <- function(
-  x,
+  model = NULL,
   panel = TRUE,
   check = "all",
   detrend = TRUE,
@@ -397,10 +408,19 @@ check_model.stanreg <- function(
   colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
   theme = see::theme_lucid(),
   verbose = FALSE,
+  x = NULL,
   ...
 ) {
+  ## TODO remove deprecation warning later
+  if (!is.null(x) && is.null(model)) {
+    insight::format_warning(
+      "Argument `x` is deprecated; please use `model` instead."
+    )
+    model <- x
+  }
+
   check_model(
-    bayestestR::bayesian_as_frequentist(x),
+    model = .safe(bayestestR::bayesian_as_frequentist(model)),
     size_dot = size_dot,
     size_line = size_line,
     panel = panel,
@@ -430,7 +450,7 @@ check_model.brmsfit <- check_model.stanreg
 
 #' @export
 check_model.model_fit <- function(
-  x,
+  model = NULL,
   panel = TRUE,
   check = "all",
   detrend = TRUE,
@@ -450,10 +470,19 @@ check_model.model_fit <- function(
   colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
   theme = see::theme_lucid(),
   verbose = FALSE,
+  x = NULL,
   ...
 ) {
+  ## TODO remove deprecation warning later
+  if (!is.null(x) && is.null(model)) {
+    insight::format_warning(
+      "Argument `x` is deprecated; please use `model` instead."
+    )
+    model <- x
+  }
+
   check_model(
-    x$fit,
+    model$fit,
     size_dot = size_dot,
     size_line = size_line,
     panel = panel,
@@ -479,7 +508,7 @@ check_model.model_fit <- function(
 
 #' @export
 check_model.performance_simres <- function(
-  x,
+  model = NULL,
   panel = TRUE,
   check = "all",
   detrend = TRUE,
@@ -499,10 +528,19 @@ check_model.performance_simres <- function(
   colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
   theme = see::theme_lucid(),
   verbose = FALSE,
+  x = NULL,
   ...
 ) {
+  ## TODO remove deprecation warning later
+  if (!is.null(x) && is.null(model)) {
+    insight::format_warning(
+      "Argument `x` is deprecated; please use `model` instead."
+    )
+    model <- x
+  }
+
   check_model(
-    x$fittedModel,
+    model$fittedModel,
     size_dot = size_dot,
     size_line = size_line,
     panel = panel,
diff --git a/R/check_predictions.R b/R/check_predictions.R
index a61f88e49..aac99c3f3 100644
--- a/R/check_predictions.R
+++ b/R/check_predictions.R
@@ -14,7 +14,7 @@
 #'   If `check_predictions()` doesn't work as expected, try setting
 #'   `verbose = TRUE` to get hints about possible problems.
 #'
-#' @param object A statistical model.
+#' @param model A statistical model.
 #' @param iterations The number of draws to simulate/bootstrap.
 #' @param check_range Logical, if `TRUE`, includes a plot with the minimum
 #'   value of the original response against the minimum values of the replicated
@@ -36,7 +36,10 @@
 #' options are appropriate for models with discrete - binary, integer or ordinal
 #' etc. - outcomes).
 #' @param verbose Toggle warnings.
-#' @param ... Passed down to `simulate()`.
+#' @param ... Additional arguments passed on to downstream functions. For
+#' frequentist models, these are forwarded to `simulate()`; for Bayesian models
+#' (e.g., `stanreg`, `brmsfit`), they are forwarded to `bayesplot::pp_check()`.
+#' @param object Deprecated, please use `model` instead.
 #'
 #' @return A data frame of simulated responses and the original response vector.
 #'
@@ -92,34 +95,44 @@
 #' check_predictions(model, type = "discrete_both")
 #'
 #' @export
-check_predictions <- function(object, ...) {
+check_predictions <- function(model = NULL, ...) {
   UseMethod("check_predictions")
 }
 
 #' @rdname check_predictions
 #' @export
 check_predictions.default <- function(
-  object,
+  model = NULL,
   iterations = 50,
   check_range = FALSE,
   re_formula = NULL,
   bandwidth = "nrd",
   type = "density",
   verbose = TRUE,
+  object = NULL,
   ...
 ) {
-  .is_model_valid(object)
+  ## TODO remove deprecation warning later
+  if (!is.null(object) && is.null(model)) {
+    insight::format_warning(
+      "Argument `object` is deprecated; please use `model` instead."
+    )
+    model <- object
+  }
+
+  .is_model_valid(model)
+
   # check_predictions() can't handle exotic formula notation
   if (verbose) {
     insight::formula_ok(
-      object,
+      model,
       action = "error",
       prefix_msg = "Posterior predictive checks failed due to an incompatible model formula." # nolint
     )
   }
 
   # retrieve model information
-  minfo <- insight::model_info(object, verbose = FALSE)
+  minfo <- insight::model_info(model, verbose = FALSE)
 
   # try to find sensible default for "type" argument
   suggest_dots <- (minfo$is_bernoulli ||
@@ -138,7 +151,7 @@ check_predictions.default <- function(
   )
 
   pp_check.lm(
-    object,
+    model,
     iterations = iterations,
     check_range = check_range,
     re_formula = re_formula,
@@ -153,17 +166,26 @@ check_predictions.default <- function(
 
 #' @export
 check_predictions.stanreg <- function(
-  object,
+  model = NULL,
   iterations = 50,
   check_range = FALSE,
   re_formula = NULL,
   bandwidth = "nrd",
   type = "density",
   verbose = TRUE,
+  object = NULL,
   ...
 ) {
+  ## TODO remove deprecation warning later
+  if (!is.null(object) && is.null(model)) {
+    insight::format_warning(
+      "Argument `object` is deprecated; please use `model` instead."
+    )
+    model <- object
+  }
+
   # retrieve model information
-  minfo <- insight::model_info(object, verbose = FALSE)
+  minfo <- insight::model_info(model, verbose = FALSE)
 
   # try to find sensible default for "type" argument
   suggest_dots <- (minfo$is_bernoulli ||
@@ -190,15 +212,15 @@ check_predictions.stanreg <- function(
   )
 
   # for plotting
-  resp_string <- insight::find_terms(object)$response
+  resp_string <- insight::find_terms(model)$response
 
-  if (inherits(object, "brmsfit")) {
+  if (inherits(model, "brmsfit")) {
     out <- as.data.frame(
-      bayesplot::pp_check(object, type = pp_type, ndraws = iterations, ...)$data
+      bayesplot::pp_check(model, type = pp_type, ndraws = iterations, ...)$data
     )
   } else {
     out <- as.data.frame(
-      bayesplot::pp_check(object, plotfun = pp_type, nreps = iterations, ...)$data
+      bayesplot::pp_check(model, plotfun = pp_type, nreps = iterations, ...)$data
     )
   }
 
@@ -247,15 +269,24 @@ check_predictions.brmsfit <- check_predictions.stanreg
 
 #' @export
 check_predictions.BFBayesFactor <- function(
-  object,
+  model = NULL,
   iterations = 50,
   check_range = FALSE,
   re_formula = NULL,
   bandwidth = "nrd",
   verbose = TRUE,
+  object = NULL,
   ...
 ) {
-  everything_we_need <- .get_bfbf_predictions(object, iterations = iterations)
+  ## TODO remove deprecation warning later
+  if (!is.null(object) && is.null(model)) {
+    insight::format_warning(
+      "Argument `object` is deprecated; please use `model` instead."
+    )
+    model <- object
+  }
+
+  everything_we_need <- .get_bfbf_predictions(model, iterations = iterations)
 
   y <- everything_we_need[["y"]]
   sig <- everything_we_need[["sigma"]]
@@ -284,7 +315,7 @@ pp_check.BFBayesFactor <- check_predictions.BFBayesFactor
 
 
 #' @export
-check_predictions.lme <- function(object, ...) {
+check_predictions.lme <- function(model = NULL, ...) {
   insight::format_error(
     "`check_predictions()` does currently not work for models of class `lme`."
   )
diff --git a/man/check_convergence.Rd b/man/check_convergence.Rd
index 55f363de1..08c7dc366 100644
--- a/man/check_convergence.Rd
+++ b/man/check_convergence.Rd
@@ -4,14 +4,16 @@
 \alias{check_convergence}
 \title{Convergence test for mixed effects models}
 \usage{
-check_convergence(x, tolerance = 0.001, ...)
+check_convergence(model = NULL, tolerance = 0.001, x = NULL, ...)
 }
 \arguments{
-\item{x}{A \code{merMod} or \code{glmmTMB}-object.}
+\item{model}{A \code{merMod} or \code{glmmTMB}-object.}
 
 \item{tolerance}{Indicates up to which value the convergence result is
 accepted. The smaller \code{tolerance} is, the stricter the test will be.}
 
+\item{x}{Deprecated, please use \code{model} instead.}
+
 \item{...}{Currently not used.}
 }
 \value{
diff --git a/man/check_model.Rd b/man/check_model.Rd
index 9dd2f5266..4c4ab1688 100644
--- a/man/check_model.Rd
+++ b/man/check_model.Rd
@@ -5,10 +5,10 @@
 \alias{check_model.default}
 \title{Visual check of model assumptions}
 \usage{
-check_model(x, ...)
+check_model(model = NULL, ...)
 
 \method{check_model}{default}(
-  x,
+  model = NULL,
   panel = TRUE,
   check = "all",
   detrend = TRUE,
@@ -28,11 +28,12 @@ check_model(x, ...)
   colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
   theme = see::theme_lucid(),
   verbose = FALSE,
+  x = NULL,
   ...
 )
 }
 \arguments{
-\item{x}{A model object.}
+\item{model}{A model object.}
 
 \item{...}{Arguments passed down to the individual check functions, especially
 to \code{check_predictions()} and \code{binned_residuals()}.}
@@ -104,6 +105,8 @@ for dots, and third color for outliers or extreme values.}
 \code{theme = ggplot2::theme_dark()}.}
 
 \item{verbose}{If \code{FALSE} (default), suppress most warning messages.}
+
+\item{x}{Deprecated, please use \code{model} instead.}
 }
 \value{
 The data frame that is used for plotting.
diff --git a/man/check_predictions.Rd b/man/check_predictions.Rd
index 1195927c5..cc9f0d426 100644
--- a/man/check_predictions.Rd
+++ b/man/check_predictions.Rd
@@ -5,23 +5,26 @@
 \alias{check_predictions.default}
 \title{Posterior predictive checks}
 \usage{
-check_predictions(object, ...)
+check_predictions(model = NULL, ...)
 
 \method{check_predictions}{default}(
-  object,
+  model = NULL,
   iterations = 50,
   check_range = FALSE,
   re_formula = NULL,
   bandwidth = "nrd",
   type = "density",
   verbose = TRUE,
+  object = NULL,
   ...
 )
 }
 \arguments{
-\item{object}{A statistical model.}
+\item{model}{A statistical model.}
 
-\item{...}{Passed down to \code{simulate()}.}
+\item{...}{Additional arguments passed on to downstream functions. For
+frequentist models, these are forwarded to \code{simulate()}; for Bayesian models
+(e.g., \code{stanreg}, \code{brmsfit}), they are forwarded to \code{bayesplot::pp_check()}.}
 
 \item{iterations}{The number of draws to simulate/bootstrap.}
 
@@ -49,6 +52,8 @@ options are appropriate for models with discrete - binary, integer or ordinal
 etc. - outcomes).}
 
 \item{verbose}{Toggle warnings.}
+
+\item{object}{Deprecated, please use \code{model} instead.}
 }
 \value{
 A data frame of simulated responses and the original response vector.
diff --git a/tests/testthat/_snaps/check_collinearity.md b/tests/testthat/_snaps/check_collinearity.md
index 2772c424a..5b76de9a3 100644
--- a/tests/testthat/_snaps/check_collinearity.md
+++ b/tests/testthat/_snaps/check_collinearity.md
@@ -1,17 +1,3 @@
-# check_collinearity, ci = NULL
-
-    Code
-      out
-    Output
-      # Check for Multicollinearity
-      
-      Low Correlation
-      
-       Term VIF adj. VIF Tolerance
-          N   1        1         1
-          P   1        1         1
-          K   1        1         1
-
 # check_collinearity, hurdle/zi models w/o zi-formula
 
     Code
diff --git a/tests/testthat/_snaps/compare_performance.md b/tests/testthat/_snaps/compare_performance.md
deleted file mode 100644
index 076e60aeb..000000000
--- a/tests/testthat/_snaps/compare_performance.md
+++ /dev/null
@@ -1,83 +0,0 @@
-# compare_performance
-
-    Code
-      print(compare_performance(lm1, lm2, lm3))
-    Output
-      # Comparison of Model Performance Indices
-      
-      Name | Model | AIC (weights) | AICc (weights) | BIC (weights) |    R2
-      ---------------------------------------------------------------------
-      lm1  |    lm | 231.5 (<.001) |  231.7 (<.001) | 243.5 (<.001) | 0.619
-      lm2  |    lm | 106.2 (0.566) |  106.6 (0.611) | 121.3 (0.964) | 0.837
-      lm3  |    lm | 106.8 (0.434) |  107.6 (0.389) | 127.8 (0.036) | 0.840
-      
-      Name | R2 (adj.) |  RMSE | Sigma
-      --------------------------------
-      lm1  |     0.614 | 0.510 | 0.515
-      lm2  |     0.833 | 0.333 | 0.338
-      lm3  |     0.835 | 0.330 | 0.336
-
----
-
-    Code
-      print(compare_performance(lm1, lm2, lm3), table_width = Inf)
-    Output
-      # Comparison of Model Performance Indices
-      
-      Name | Model | AIC (weights) | AICc (weights) | BIC (weights) |    R2 | R2 (adj.) |  RMSE | Sigma
-      -------------------------------------------------------------------------------------------------
-      lm1  |    lm | 231.5 (<.001) |  231.7 (<.001) | 243.5 (<.001) | 0.619 |     0.614 | 0.510 | 0.515
-      lm2  |    lm | 106.2 (0.566) |  106.6 (0.611) | 121.3 (0.964) | 0.837 |     0.833 | 0.333 | 0.338
-      lm3  |    lm | 106.8 (0.434) |  107.6 (0.389) | 127.8 (0.036) | 0.840 |     0.835 | 0.330 | 0.336
-
----
-
-    Code
-      print(compare_performance(lm1, lm2, lm3), layout = "vertical")
-    Output
-      # Comparison of Model Performance Indices
-      
-      Metric         |           lm1 |           lm2 |           lm3
-      --------------------------------------------------------------
-      Model          |            lm |            lm |            lm
-      AIC (weights)  | 231.5 (<.001) | 106.2 (0.566) | 106.8 (0.434)
-      AICc (weights) | 231.7 (<.001) | 106.6 (0.611) | 107.6 (0.389)
-      BIC (weights)  | 243.5 (<.001) | 121.3 (0.964) | 127.8 (0.036)
-      R2             |         0.619 |         0.837 |         0.840
-      R2 (adj.)      |         0.614 |         0.833 |         0.835
-      RMSE           |         0.510 |         0.333 |         0.330
-      Sigma          |         0.515 |         0.338 |         0.336
-
----
-
-    Code
-      print(compare_performance(lm1, lm2, lm3, lm4), layout = "vertical",
-      table_width = 50)
-    Message
-      When comparing models, please note that probably not all models were fit
-        from same data.
-    Output
-      # Comparison of Model Performance Indices
-      
-      Metric         |           lm1 |           lm2
-      ----------------------------------------------
-      Model          |            lm |            lm
-      AIC (weights)  | 231.5 (<.001) | 106.2 (0.408)
-      AICc (weights) | 231.7 (<.001) | 106.6 (0.454)
-      BIC (weights)  | 243.5 (<.001) | 121.3 (0.933)
-      R2             |         0.619 |         0.837
-      R2 (adj.)      |         0.614 |         0.833
-      RMSE           |         0.510 |         0.333
-      Sigma          |         0.515 |         0.338
-      
-      Metric         |           lm3 |           lm4
-      ----------------------------------------------
-      Model          |            lm |            lm
-      AIC (weights)  | 106.8 (0.313) | 107.0 (0.279)
-      AICc (weights) | 107.6 (0.289) | 107.8 (0.257)
-      BIC (weights)  | 127.8 (0.035) | 128.0 (0.032)
-      R2             |         0.840 |         0.840
-      R2 (adj.)      |         0.835 |         0.834
-      RMSE           |         0.330 |         0.331
-      Sigma          |         0.336 |         0.337
-
diff --git a/tests/testthat/test-check_collinearity.R b/tests/testthat/test-check_collinearity.R
index 241aed097..c6b192643 100644
--- a/tests/testthat/test-check_collinearity.R
+++ b/tests/testthat/test-check_collinearity.R
@@ -205,7 +205,19 @@ test_that("check_collinearity, ci = NULL", {
       "Tolerance_CI_low", "Tolerance_CI_high"
     )
   )
-  expect_snapshot(out)
+  expect_identical(
+    capture.output(print(out)),
+    c(
+      "# Check for Multicollinearity",
+      "",
+      "Low Correlation",
+      "",
+      " Term VIF adj. VIF Tolerance",
+      "    N   1        1         1",
+      "    P   1        1         1",
+      "    K   1        1         1"
+    )
+  )
 })
 
 test_that("check_collinearity, ci are NA", {
diff --git a/tests/testthat/test-check_convergence.R b/tests/testthat/test-check_convergence.R
index 1aeb41694..f7b21e41d 100644
--- a/tests/testthat/test-check_convergence.R
+++ b/tests/testthat/test-check_convergence.R
@@ -19,6 +19,11 @@ test_that("check_convergence", {
     structure(TRUE, gradient = NA_real_),
     tolerance = 1e-3
   )
+  expect_warning(
+    check_convergence(x = model),
+    regex = "Argument `x` is deprecated",
+    fixed = TRUE
+  )
 })
 
 test_that("check_convergence", {
diff --git a/tests/testthat/test-check_model.R b/tests/testthat/test-check_model.R
index 7ee4be747..d8a157b6c 100644
--- a/tests/testthat/test-check_model.R
+++ b/tests/testthat/test-check_model.R
@@ -113,6 +113,11 @@ suppressWarnings({
 test_that("`check_model()` works if convergence issues", {
   x <- check_model(m, verbose = FALSE)
   expect_s3_class(x, "check_model")
+  expect_warning(
+    check_model(x = m, verbose = FALSE),
+    regex = "Argument `x` is deprecated",
+    fixed = TRUE
+  )
 })
 
 test_that("`check_outliers()` works if convergence issues", {
diff --git a/tests/testthat/test-compare_performance.R b/tests/testthat/test-compare_performance.R
index 3fce8c4c9..e8f965cc7 100644
--- a/tests/testthat/test-compare_performance.R
+++ b/tests/testthat/test-compare_performance.R
@@ -43,19 +43,92 @@ test_that("compare_performance", {
     )
   )
 
+  skip_on_cran()
+
   # table split
-  expect_snapshot(print(compare_performance(lm1, lm2, lm3)))
-  expect_snapshot(print(compare_performance(lm1, lm2, lm3), table_width = Inf))
+  expect_identical(
+    capture.output(print(compare_performance(lm1, lm2, lm3), table_width = 85)),
+    c(
+      "# Comparison of Model Performance Indices",
+      "",
+      "Name | Model | AIC (weights) | AICc (weights) | BIC (weights) |    R2 | R2 (adj.)",
+      "---------------------------------------------------------------------------------",
+      "lm1  |    lm | 231.5 (<.001) |  231.7 (<.001) | 243.5 (<.001) | 0.619 |     0.614",
+      "lm2  |    lm | 106.2 (0.566) |  106.6 (0.611) | 121.3 (0.964) | 0.837 |     0.833",
+      "lm3  |    lm | 106.8 (0.434) |  107.6 (0.389) | 127.8 (0.036) | 0.840 |     0.835",
+      "",
+      "Name |  RMSE | Sigma",
+      "--------------------",
+      "lm1  | 0.510 | 0.515",
+      "lm2  | 0.333 | 0.338",
+      "lm3  | 0.330 | 0.336"
+    )
+  )
+  expect_identical(
+    capture.output(print(compare_performance(lm1, lm2, lm3), table_width = Inf)),
+    c(
+      "# Comparison of Model Performance Indices",
+      "",
+      "Name | Model | AIC (weights) | AICc (weights) | BIC (weights) |    R2 | R2 (adj.) |  RMSE | Sigma",
+      "-------------------------------------------------------------------------------------------------",
+      "lm1  |    lm | 231.5 (<.001) |  231.7 (<.001) | 243.5 (<.001) | 0.619 |     0.614 | 0.510 | 0.515",
+      "lm2  |    lm | 106.2 (0.566) |  106.6 (0.611) | 121.3 (0.964) | 0.837 |     0.833 | 0.333 | 0.338",
+      "lm3  |    lm | 106.8 (0.434) |  107.6 (0.389) | 127.8 (0.036) | 0.840 |     0.835 | 0.330 | 0.336"
+    )
+  )
   # vertical layout
-  expect_snapshot(print(compare_performance(lm1, lm2, lm3), layout = "vertical"))
-  expect_snapshot(print(
-    compare_performance(lm1, lm2, lm3, lm4),
-    layout = "vertical",
-    table_width = 50
-  ))
+  expect_identical(
+    capture.output(print(compare_performance(lm1, lm2, lm3), layout = "vertical")),
+    c(
+      "# Comparison of Model Performance Indices",
+      "",
+      "Metric         |           lm1 |           lm2 |           lm3",
+      "--------------------------------------------------------------",
+      "Model          |            lm |            lm |            lm",
+      "AIC (weights)  | 231.5 (<.001) | 106.2 (0.566) | 106.8 (0.434)",
+      "AICc (weights) | 231.7 (<.001) | 106.6 (0.611) | 107.6 (0.389)",
+      "BIC (weights)  | 243.5 (<.001) | 121.3 (0.964) | 127.8 (0.036)",
+      "R2             |         0.619 |         0.837 |         0.840",
+      "R2 (adj.)      |         0.614 |         0.833 |         0.835",
+      "RMSE           |         0.510 |         0.333 |         0.330",
+      "Sigma          |         0.515 |         0.338 |         0.336"
+    )
+  )
+  expect_identical(
+    capture.output(print(
+      compare_performance(lm1, lm2, lm3, lm4),
+      layout = "vertical",
+      table_width = 50
+    )),
+    c(
+      "# Comparison of Model Performance Indices",
+      "",
+      "Metric         |           lm1 |           lm2",
+      "----------------------------------------------",
+      "Model          |            lm |            lm",
+      "AIC (weights)  | 231.5 (<.001) | 106.2 (0.408)",
+      "AICc (weights) | 231.7 (<.001) | 106.6 (0.454)",
+      "BIC (weights)  | 243.5 (<.001) | 121.3 (0.933)",
+      "R2             |         0.619 |         0.837",
+      "R2 (adj.)      |         0.614 |         0.833",
+      "RMSE           |         0.510 |         0.333",
+      "Sigma          |         0.515 |         0.338",
+      "",
+      "Metric         |           lm3 |           lm4",
+      "----------------------------------------------",
+      "Model          |            lm |            lm",
+      "AIC (weights)  | 106.8 (0.313) | 107.0 (0.279)",
+      "AICc (weights) | 107.6 (0.289) | 107.8 (0.257)",
+      "BIC (weights)  | 127.8 (0.035) | 128.0 (0.032)",
+      "R2             |         0.840 |         0.840",
+      "R2 (adj.)      |         0.835 |         0.834",
+      "RMSE           |         0.330 |         0.331",
+      "Sigma          |         0.336 |         0.337"
+    )
+  )
 
-  expect_silent(expect_identical(
-    colnames(compare_performance(lm1, lm2, lm3, lm4, verbose = FALSE)),
+  expect_silent(expect_named(
+    compare_performance(lm1, lm2, lm3, lm4, verbose = FALSE),
     c(
       "Name",
       "Model",
@@ -84,8 +157,8 @@ test_that("compare_performance", {
   )
 
   out <- compare_performance(list(lm1, lm2, lm3, lm4), verbose = FALSE)
-  expect_identical(
-    colnames(out),
+  expect_named(
+    out,
     c(
       "Name",
       "Model",
@@ -105,8 +178,8 @@ test_that("compare_performance", {
 
   models <- list(lm1, lm2, lm3, lm4)
   out <- compare_performance(models, verbose = FALSE)
-  expect_identical(
-    colnames(out),
+  expect_named(
+    out,
     c(
       "Name",
       "Model",