diff --git a/DESCRIPTION b/DESCRIPTION
index 929c66db8..b16d757e7 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.21.3.2
+Version: 0.21.3.3
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -146,6 +146,7 @@ Suggests:
     lme4,
     lmerTest,
     lmtest,
+    logistf,
     logspline,
     lqmm,
     M3C,
diff --git a/NEWS.md b/NEWS.md
index 58c32e1bd..778eb912a 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -6,6 +6,11 @@
   `marginaleffects::predictions()` now defaults to `FALSE`, in line with all
   the other `model_parameters()` methods.
 
+## Changes
+
+* `model_parameters()` for models of package *survey* now gives informative
+  messages when `bootstrap = TRUE` (which is currently not supported).
+
 # parameters 0.21.3
 
 ## Changes
diff --git a/R/1_model_parameters.R b/R/1_model_parameters.R
index 0113673b7..aa8106750 100644
--- a/R/1_model_parameters.R
+++ b/R/1_model_parameters.R
@@ -576,14 +576,14 @@ model_parameters.default <- function(model,
       ci_method <- "quantile"
     }
 
-    args <- list(
+    fun_args <- list(
       model,
       iterations = iterations,
       ci = ci,
       ci_method = ci_method
     )
-    args <- c(args, dots)
-    params <- do.call("bootstrap_parameters", args)
+    fun_args <- c(fun_args, dots)
+    params <- do.call("bootstrap_parameters", fun_args)
 
     # Processing, non-bootstrapped parameters
   } else {
@@ -592,7 +592,7 @@ model_parameters.default <- function(model,
       ci_method <- "wald"
     }
 
-    args <- list(
+    fun_args <- list(
       model,
       ci = ci,
       component = component,
@@ -607,8 +607,8 @@ model_parameters.default <- function(model,
       vcov = vcov,
       vcov_args = vcov_args
     )
-    args <- c(args, dots)
-    params <- do.call(".extract_parameters_generic", args)
+    fun_args <- c(fun_args, dots)
+    params <- do.call(".extract_parameters_generic", fun_args)
   }
 
 
@@ -686,12 +686,12 @@ model_parameters.glm <- function(model,
   # tell user that profiled CIs don't respect vcov-args
   if (identical(ci_method, "profile") && (!is.null(vcov) || !is.null(vcov_args)) && isTRUE(verbose)) {
     insight::format_alert(
-      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.",
+      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.", # nolint
       "Use `ci_method=\"wald\"` to return confidence intervals based on robust standard errors."
     )
   }
 
-  args <- list(
+  fun_args <- list(
     model = model,
     ci = ci,
     ci_method = ci_method,
@@ -708,8 +708,8 @@ model_parameters.glm <- function(model,
     vcov_args = vcov_args,
     verbose = verbose
   )
-  args <- c(args, dots)
-  out <- do.call(".model_parameters_generic", args)
+  fun_args <- c(fun_args, dots)
+  out <- do.call(".model_parameters_generic", fun_args)
 
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
diff --git a/R/3_p_value.R b/R/3_p_value.R
index fca6d150e..a357443f2 100644
--- a/R/3_p_value.R
+++ b/R/3_p_value.R
@@ -105,13 +105,13 @@ p_value.default <- function(model,
     if (inherits(vcov, "data.frame") || "SE" %in% colnames(vcov)) {
       se <- vcov
     } else {
-      args <- list(model,
+      fun_args <- list(model,
         vcov_args = vcov_args,
         vcov = vcov,
         verbose = verbose
       )
-      args <- c(args, dots)
-      se <- do.call("standard_error", args)
+      fun_args <- c(fun_args, dots)
+      se <- do.call("standard_error", fun_args)
     }
 
     dof <- degrees_of_freedom(model, method = "wald", verbose = FALSE)
diff --git a/R/4_standard_error.R b/R/4_standard_error.R
index e6b1e5d46..6dc4b0292 100644
--- a/R/4_standard_error.R
+++ b/R/4_standard_error.R
@@ -88,8 +88,8 @@ standard_error.default <- function(model,
 
   # vcov: function which returns a matrix
   if (is.function(vcov)) {
-    args <- c(list(model), vcov_args, dots)
-    se <- .safe(sqrt(diag(do.call("vcov", args))))
+    fun_args <- c(list(model), vcov_args, dots)
+    se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
   }
 
   # vcov: character (with backward compatibility for `robust = TRUE`)
diff --git a/R/ci_profile_boot.R b/R/ci_profile_boot.R
index 0dab03861..6dfc4bbb2 100644
--- a/R/ci_profile_boot.R
+++ b/R/ci_profile_boot.R
@@ -84,14 +84,14 @@
   dot_args <- .check_profile_uniroot_args(...)
 
   if (is.null(profiled)) {
-    args <- list(x, method = "profile", level = ci, dot_args)
-    out <- as.data.frame(do.call(stats::confint, args))
+    fun_args <- list(x, method = "profile", level = ci, dot_args)
+    out <- as.data.frame(do.call(stats::confint, fun_args))
   } else {
-    args <- list(profiled, level = ci, dot_args)
-    out <- .safe(as.data.frame(do.call(stats::confint, args)))
+    fun_args <- list(profiled, level = ci, dot_args)
+    out <- .safe(as.data.frame(do.call(stats::confint, fun_args)))
     if (is.null(out)) {
-      args <- list(x, method = "profile", level = ci, dot_args)
-      out <- as.data.frame(do.call(stats::confint, args))
+      fun_args <- list(x, method = "profile", level = ci, dot_args)
+      out <- as.data.frame(do.call(stats::confint, fun_args))
     }
   }
   .process_glmmTMB_CI(x, out, ci, component)
@@ -103,8 +103,8 @@
 .ci_uniroot_glmmTMB <- function(x, ci, component, ...) {
   # make sure "..." doesn't pass invalid arguments to package TMB
   dot_args <- .check_profile_uniroot_args(...)
-  args <- list(x, level = ci, method = "uniroot", dot_args)
-  out <- as.data.frame(do.call(stats::confint, args))
+  fun_args <- list(x, level = ci, method = "uniroot", dot_args)
+  out <- as.data.frame(do.call(stats::confint, fun_args))
   .process_glmmTMB_CI(x, out, ci, component)
 }
 
diff --git a/R/dominance_analysis.R b/R/dominance_analysis.R
index 90d991ecb..efeb46e59 100644
--- a/R/dominance_analysis.R
+++ b/R/dominance_analysis.R
@@ -347,11 +347,10 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
 
   # quote arguments for domin
   for (arg in quote_args) {
-    if (!(arg %in% names(args))) {
-      insight::format_error(arg, " in `quote_args` not among arguments in model.")
+    if (arg %in% names(args)) {
+      args[[arg]] <- str2lang(paste0("quote(", deparse(args[[arg]]), ")", collapse = ""))
     } else {
-      args[[arg]] <-
-        str2lang(paste0("quote(", deparse(args[[arg]]), ")", collapse = ""))
+      insight::format_error(arg, " in `quote_args` not among arguments in model.")
     }
   }
 
diff --git a/R/extract_parameters.R b/R/extract_parameters.R
index 61411246c..997e75938 100644
--- a/R/extract_parameters.R
+++ b/R/extract_parameters.R
@@ -43,12 +43,11 @@
   # ==== for refit, we completely refit the model, than extract parameters, ci etc. as usual
 
   if (isTRUE(standardize == "refit")) {
-    args <- list(model, verbose = FALSE)
-    args <- c(args, list(...))
+    fun_args <- c(list(model, verbose = FALSE), dots)
     # argument name conflict with deprecated `robust`
-    args[["robust"]] <- NULL
+    fun_args[["robust"]] <- NULL
     fun <- datawizard::standardize
-    model <- do.call(fun, args)
+    model <- do.call(fun, fun_args)
   }
 
   parameters <- insight::get_parameters(model,
@@ -80,7 +79,7 @@
   #      intercepts (alpha-coefficients) in the component column
 
   if (inherits(model, "polr")) {
-    intercept_groups <- which(grepl("Intercept:", parameters$Parameter, fixed = TRUE))
+    intercept_groups <- grep("Intercept:", parameters$Parameter, fixed = TRUE)
     parameters$Parameter <- gsub("Intercept: ", "", parameters$Parameter, fixed = TRUE)
   } else if (inherits(model, "clm") && !is.null(model$alpha)) {
     intercept_groups <- rep(
@@ -104,21 +103,25 @@
 
   # ==== CI - only if we don't already have CI for std. parameters
 
-  if (!is.null(ci)) {
-    args <- list(model,
+  if (is.null(ci)) {
+    ci_cols <- NULL
+  } else {
+    fun_args <- list(model,
       ci = ci,
       component = component,
       vcov = vcov,
       vcov_args = vcov_args,
       verbose = verbose
     )
-    args <- c(args, dots)
+    fun_args <- c(fun_args, dots)
     if (!is.null(ci_method)) {
-      args[["method"]] <- ci_method
+      fun_args[["method"]] <- ci_method
     }
-    ci_df <- suppressMessages(do.call("ci", args))
+    ci_df <- suppressMessages(do.call("ci", fun_args))
 
-    if (!is.null(ci_df)) {
+    if (is.null(ci_df)) {
+      ci_cols <- NULL
+    } else {
       # for multiple CI columns, reshape CI-dataframe to match parameters df
       if (length(ci) > 1) {
         ci_df <- datawizard::reshape_ci(ci_df)
@@ -126,17 +129,13 @@
       # remember names of CI columns, used for later sorting of columns
       ci_cols <- names(ci_df)[!names(ci_df) %in% c("CI", merge_by)]
       parameters <- merge(parameters, ci_df, by = merge_by, sort = FALSE)
-    } else {
-      ci_cols <- NULL
     }
-  } else {
-    ci_cols <- NULL
   }
 
 
   # ==== p value
 
-  args <- list(model,
+  fun_args <- list(model,
     method = ci_method,
     effects = effects,
     verbose = verbose,
@@ -144,8 +143,8 @@
     vcov = vcov,
     vcov_args = vcov_args
   )
-  args <- c(args, dots)
-  pval <- do.call("p_value", args)
+  fun_args <- c(fun_args, dots)
+  pval <- do.call("p_value", fun_args)
 
   if (!is.null(pval)) {
     parameters <- merge(parameters, pval, by = merge_by, sort = FALSE)
@@ -155,18 +154,18 @@
   # ==== standard error - only if we don't already have SE for std. parameters
 
   std_err <- NULL
-  args <- list(model,
+  fun_args <- list(model,
     effects = effects,
     component = component,
     verbose = verbose,
     vcov = vcov,
     vcov_args = vcov_args
   )
-  args <- c(args, dots)
+  fun_args <- c(fun_args, dots)
   if (!is.null(ci_method)) {
-    args[["method"]] <- ci_method
+    fun_args[["method"]] <- ci_method
   }
-  std_err <- do.call("standard_error", args)
+  std_err <- do.call("standard_error", fun_args)
 
   if (!is.null(std_err)) {
     parameters <- merge(parameters, std_err, by = merge_by, sort = FALSE)
@@ -186,10 +185,10 @@
 
   # ==== degrees of freedom
 
-  if (!is.null(ci_method)) {
-    df_error <- degrees_of_freedom(model, method = ci_method, verbose = FALSE)
-  } else {
+  if (is.null(ci_method)) {
     df_error <- degrees_of_freedom(model, method = "any", verbose = FALSE)
+  } else {
+    df_error <- degrees_of_freedom(model, method = ci_method, verbose = FALSE)
   }
   if (!is.null(df_error) && (length(df_error) == 1 || length(df_error) == nrow(parameters))) {
     if (length(df_error) == 1) {
@@ -232,8 +231,8 @@
 
   # ==== remove Component column if not needed
 
-  if (!is.null(parameters$Component) && insight::n_unique(parameters$Component) == 1 && !keep_component_column) parameters$Component <- NULL
-  if ((!is.null(parameters$Effects) && insight::n_unique(parameters$Effects) == 1) || effects == "fixed") parameters$Effects <- NULL
+  if (!is.null(parameters$Component) && insight::n_unique(parameters$Component) == 1 && !keep_component_column) parameters$Component <- NULL # nolint
+  if ((!is.null(parameters$Effects) && insight::n_unique(parameters$Effects) == 1) || effects == "fixed") parameters$Effects <- NULL # nolint
 
 
   # ==== filter parameters, if requested
@@ -383,16 +382,16 @@
   }
 
   # row to keep and drop
-  if (!is.null(keep)) {
-    rows_to_keep <- grepl(keep, params[[column]], perl = TRUE)
-  } else {
+  if (is.null(keep)) {
     rows_to_keep <- rep_len(TRUE, nrow(params))
+  } else {
+    rows_to_keep <- grepl(keep, params[[column]], perl = TRUE)
   }
 
-  if (!is.null(drop)) {
-    rows_to_drop <- !grepl(drop, params[[column]], perl = TRUE)
-  } else {
+  if (is.null(drop)) {
     rows_to_drop <- rep_len(TRUE, nrow(params))
+  } else {
+    rows_to_drop <- !grepl(drop, params[[column]], perl = TRUE)
   }
 
 
@@ -401,7 +400,7 @@
   if (nrow(out) == 0) {
     if (verbose) {
       insight::format_alert(
-        "The pattern defined in the `keep` (and `drop`) arguments would remove all parameters from the output. Thus, selecting specific parameters will be ignored."
+        "The pattern defined in the `keep` (and `drop`) arguments would remove all parameters from the output. Thus, selecting specific parameters will be ignored." # nolint
       )
     }
     return(params)
@@ -452,33 +451,35 @@
 
   # Degrees of freedom
   if (.dof_method_ok(model, ci_method)) {
-    df <- degrees_of_freedom(model, method = ci_method, verbose = FALSE)
+    dof <- degrees_of_freedom(model, method = ci_method, verbose = FALSE)
   } else {
-    df <- Inf
+    dof <- Inf
   }
 
   df_error <- data.frame(
     Parameter = parameters$Parameter,
-    df_error = as.vector(df),
+    df_error = as.vector(dof),
     stringsAsFactors = FALSE
   )
   # for KR-dof, we have the SE as well, to save computation time
-  df_error$SE <- attr(df, "se", exact = TRUE)
+  df_error$SE <- attr(dof, "se", exact = TRUE)
 
 
   # CI - only if we don't already have CI for std. parameters
 
-  if (!is.null(ci)) {
+  if (is.null(ci)) {
+    ci_cols <- NULL
+  } else {
     # robust (current or deprecated)
     if (!is.null(vcov) || isTRUE(list(...)[["robust"]])) {
-      args <- list(model,
+      fun_args <- list(model,
         ci = ci,
         vcov = vcov,
         vcov_args = vcov_args,
         verbose = verbose
       )
-      args <- c(args, dots)
-      ci_df <- suppressMessages(do.call("ci", args))
+      fun_args <- c(fun_args, dots)
+      ci_df <- suppressMessages(do.call("ci", fun_args))
     } else if (ci_method %in% c("kenward", "kr")) {
       # special handling for KR-CIs, where we already have computed SE
       ci_df <- .ci_kenward_dof(model, ci = ci, df_kr = df_error)
@@ -488,21 +489,19 @@
     if (length(ci) > 1) ci_df <- datawizard::reshape_ci(ci_df)
     ci_cols <- names(ci_df)[!names(ci_df) %in% c("CI", "Parameter")]
     parameters <- merge(parameters, ci_df, by = "Parameter", sort = FALSE)
-  } else {
-    ci_cols <- NULL
   }
 
 
   # standard error - only if we don't already have SE for std. parameters
   if (!"SE" %in% colnames(parameters)) {
     if (!is.null(vcov) || isTRUE(dots[["robust"]])) {
-      args <- list(model,
+      fun_args <- list(model,
         vcov = vcov,
         vcov_args = vcov_args,
         verbose = verbose
       )
-      args <- c(args, dots)
-      parameters <- merge(parameters, do.call("standard_error", args), by = "Parameter", sort = FALSE)
+      fun_args <- c(fun_args, dots)
+      parameters <- merge(parameters, do.call("standard_error", fun_args), by = "Parameter", sort = FALSE)
       # special handling for KR-SEs, which we already have computed from dof
     } else if ("SE" %in% colnames(df_error)) {
       se_kr <- df_error
@@ -521,13 +520,13 @@
 
   # p value
   if (!is.null(vcov) || isTRUE(list(...)[["robust"]])) {
-    args <- list(model,
+    fun_args <- list(model,
       vcov = vcov,
       vcov_args = vcov_args,
       verbose = verbose
     )
-    args <- c(args, dots)
-    parameters <- merge(parameters, do.call("p_value", args), by = "Parameter", sort = FALSE)
+    fun_args <- c(fun_args, dots)
+    parameters <- merge(parameters, do.call("p_value", fun_args), by = "Parameter", sort = FALSE)
   } else {
     if ("Pr(>|z|)" %in% names(parameters)) {
       names(parameters)[grepl("Pr(>|z|)", names(parameters), fixed = TRUE)] <- "p"
@@ -543,7 +542,7 @@
     } else {
       parameters <- merge(
         parameters,
-        p_value(model, dof = df, effects = "fixed"),
+        p_value(model, dof = dof, effects = "fixed"),
         by = "Parameter",
         sort = FALSE
       )
@@ -635,8 +634,8 @@
   }
 
   # Reorder
-  order <- c("Parameter", coef_col, "SE", ci_cols, "t", "z", "df", "df_error", "p", "Component")
-  parameters <- parameters[order[order %in% names(parameters)]]
+  col_order <- c("Parameter", coef_col, "SE", ci_cols, "t", "z", "df", "df_error", "p", "Component")
+  parameters <- parameters[col_order[col_order %in% names(parameters)]]
 
 
   # add sigma
@@ -765,7 +764,23 @@
       verbose = verbose,
       ...
     )
-  } else if (!is.null(standardize)) {
+  } else if (is.null(standardize)) {
+    parameters <- bayestestR::describe_posterior(
+      model,
+      centrality = centrality,
+      dispersion = dispersion,
+      ci = ci,
+      ci_method = ci_method,
+      test = test,
+      rope_range = rope_range,
+      rope_ci = rope_ci,
+      bf_prior = bf_prior,
+      diagnostic = diagnostic,
+      priors = priors,
+      verbose = verbose,
+      ...
+    )
+  } else {
     parameters <- bayestestR::describe_posterior(
       model,
       centrality = centrality,
@@ -804,22 +819,6 @@
       parameters[c("Parameter", setdiff(colnames(parameters), colnames(std_parameters)))],
       sort = FALSE
     )
-  } else {
-    parameters <- bayestestR::describe_posterior(
-      model,
-      centrality = centrality,
-      dispersion = dispersion,
-      ci = ci,
-      ci_method = ci_method,
-      test = test,
-      rope_range = rope_range,
-      rope_ci = rope_ci,
-      bf_prior = bf_prior,
-      diagnostic = diagnostic,
-      priors = priors,
-      verbose = verbose,
-      ...
-    )
   }
 
   if (length(ci) > 1) {
@@ -886,7 +885,7 @@
   if (!is.logical(standardize) && !(standardize %in% valid_std_options)) {
     if (verbose) {
       insight::format_alert(
-        "`standardize` should be one of `TRUE`, \"all\", \"std.all\", \"latent\", \"std.lv\", \"no_exogenous\" or \"std.nox\".",
+        "`standardize` should be one of `TRUE`, \"all\", \"std.all\", \"latent\", \"std.lv\", \"no_exogenous\" or \"std.nox\".", # nolint
         "Returning unstandardized solution."
       )
     }
@@ -928,7 +927,7 @@
   )]
 
   # Get estimates
-  data <- do.call(
+  sem_data <- do.call(
     lavaan::parameterEstimates,
     c(
       list(object = model, se = TRUE, ci = TRUE, level = ci),
@@ -936,7 +935,7 @@
     )
   )
 
-  label <- data$label
+  label <- sem_data$label
 
   # check if standardized estimates are requested, and if so, which type
   if (isTRUE(standardize) || !is.logical(standardize)) {
@@ -958,23 +957,23 @@
     valid <- names(formals(lavaan::standardizedsolution))
     dots <- list(...)
     dots <- dots[names(dots) %in% valid]
-    args <- c(list(model, se = TRUE, level = ci, type = type), dots)
+    fun_args <- c(list(model, se = TRUE, level = ci, type = type), dots)
     f <- utils::getFromNamespace("standardizedsolution", "lavaan")
-    data <- do.call("f", args)
-    names(data)[names(data) == "est.std"] <- "est"
+    sem_data <- do.call("f", fun_args)
+    names(sem_data)[names(sem_data) == "est.std"] <- "est"
   }
 
 
   params <- data.frame(
-    To = data$lhs,
-    Operator = data$op,
-    From = data$rhs,
-    Coefficient = data$est,
-    SE = data$se,
-    CI_low = data$ci.lower,
-    CI_high = data$ci.upper,
-    z = data$z,
-    p = data$pvalue,
+    To = sem_data$lhs,
+    Operator = sem_data$op,
+    From = sem_data$rhs,
+    Coefficient = sem_data$est,
+    SE = sem_data$se,
+    CI_low = sem_data$ci.lower,
+    CI_high = sem_data$ci.upper,
+    z = sem_data$z,
+    p = sem_data$pvalue,
     stringsAsFactors = FALSE
   )
 
@@ -995,8 +994,8 @@
     params$p[is.na(params$p)] <- 0
   }
 
-  if ("group" %in% names(data)) {
-    params$Group <- data$group
+  if ("group" %in% names(sem_data)) {
+    params$Group <- sem_data$group
   }
 
   # filter parameters, if requested
diff --git a/R/methods_betareg.R b/R/methods_betareg.R
index dbc8451ac..4c4ce273b 100644
--- a/R/methods_betareg.R
+++ b/R/methods_betareg.R
@@ -32,7 +32,7 @@ model_parameters.betareg <- function(model,
 
   ## TODO check merge by
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     component = component,
@@ -48,9 +48,9 @@ model_parameters.betareg <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }
diff --git a/R/methods_brglm2.R b/R/methods_brglm2.R
index 2b6c0cdf2..2b9eb4ca9 100644
--- a/R/methods_brglm2.R
+++ b/R/methods_brglm2.R
@@ -45,7 +45,7 @@ model_parameters.bracl <- function(model,
     merge_by <- "Parameter"
   }
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     bootstrap = bootstrap,
@@ -60,9 +60,9 @@ model_parameters.bracl <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }
@@ -198,22 +198,22 @@ degrees_of_freedom.nnet <- degrees_of_freedom.multinom
 standard_error.multinom <- function(model, ...) {
   se <- tryCatch(
     {
-      stderr <- summary(model)$standard.errors
-      if (is.null(stderr)) {
+      std_err <- summary(model)$standard.errors
+      if (is.null(std_err)) {
         vc <- insight::get_varcov(model)
-        stderr <- as.vector(sqrt(diag(vc)))
+        std_err <- as.vector(sqrt(diag(vc)))
       } else {
-        if (is.matrix(stderr)) {
+        if (is.matrix(std_err)) {
           tmp <- NULL
-          for (i in seq_len(nrow(stderr))) {
-            tmp <- c(tmp, as.vector(stderr[i, ]))
+          for (i in seq_len(nrow(std_err))) {
+            tmp <- c(tmp, as.vector(std_err[i, ]))
           }
         } else {
-          tmp <- as.vector(stderr)
+          tmp <- as.vector(std_err)
         }
-        stderr <- tmp
+        std_err <- tmp
       }
-      stderr
+      std_err
     },
     error = function(e) {
       vc <- insight::get_varcov(model)
@@ -257,9 +257,9 @@ simulate_parameters.multinom <- function(model,
                                          ci_method = "quantile",
                                          test = "p-value",
                                          ...) {
-  data <- simulate_model(model, iterations = iterations, ...)
+  sim_data <- simulate_model(model, iterations = iterations, ...)
   out <- .summary_bootstrap(
-    data = data,
+    data = sim_data,
     test = test,
     centrality = centrality,
     ci = ci,
diff --git a/R/methods_car.R b/R/methods_car.R
index 1de7f01c6..0284cb283 100644
--- a/R/methods_car.R
+++ b/R/methods_car.R
@@ -3,7 +3,7 @@ model_parameters.deltaMethod <- function(model, p_adjust = NULL, verbose = TRUE,
   dots <- list(...)
   if ("ci" %in% names(dots)) {
     insight::format_warning(
-      "The `ci` argument is not supported by `model_parameters` for objects of this class. Use the `level` argument of the `deltaMethod` function instead."
+      "The `ci` argument is not supported by `model_parameters` for objects of this class. Use the `level` argument of the `deltaMethod` function instead." # nolint
     )
     dots[["ci"]] <- NULL
   }
@@ -37,7 +37,7 @@ model_parameters.deltaMethod <- function(model, p_adjust = NULL, verbose = TRUE,
     params <- .p_adjust(params, p_adjust, model, verbose)
   }
 
-  args <- list(
+  fun_args <- list(
     params,
     model,
     ci = ci,
@@ -49,9 +49,9 @@ model_parameters.deltaMethod <- function(model, p_adjust = NULL, verbose = TRUE,
     summary = FALSE,
     verbose = verbose
   )
-  args <- c(args, dots)
+  fun_args <- c(fun_args, dots)
 
-  params <- do.call(".add_model_parameters_attributes", args)
+  params <- do.call(".add_model_parameters_attributes", fun_args)
 
   class(params) <- c("parameters_model", "see_parameters_model", class(params))
   attr(params, "object_name") <- insight::safe_deparse_symbol(substitute(model))
diff --git a/R/methods_cgam.R b/R/methods_cgam.R
index 661dbf2e4..a70416cd2 100644
--- a/R/methods_cgam.R
+++ b/R/methods_cgam.R
@@ -60,7 +60,7 @@ model_parameters.cgam <- function(model,
       ...
     )
   } else {
-    args <- list(
+    fun_args <- list(
       model,
       ci = ci,
       ci_method = ci_method,
@@ -74,8 +74,8 @@ model_parameters.cgam <- function(model,
       vcov = NULL,
       vcov_args = NULL
     )
-    args <- c(args, dot_args)
-    params <- do.call(".extract_parameters_generic", args)
+    fun_args <- c(fun_args, dot_args)
+    params <- do.call(".extract_parameters_generic", fun_args)
   }
 
   # fix statistic column
@@ -84,7 +84,7 @@ model_parameters.cgam <- function(model,
   }
 
   # fix estimated df column
-  if (inherits(model, c("gam", "cgam", "scam", "rqss")) && "smooth_terms" %in% params$Component && !("df" %in% names(params))) {
+  if (inherits(model, c("gam", "cgam", "scam", "rqss")) && "smooth_terms" %in% params$Component && !("df" %in% names(params))) { # nolint
     params$df <- params$Coefficient
     params$df[params$Component != "smooth_terms"] <- NA
     params$df_error[params$Component == "smooth_terms"] <- NA
diff --git a/R/methods_glmmTMB.R b/R/methods_glmmTMB.R
index 9738c947b..ccef7de94 100644
--- a/R/methods_glmmTMB.R
+++ b/R/methods_glmmTMB.R
@@ -81,7 +81,7 @@ model_parameters.glmmTMB <- function(model,
         }
       }
     } else {
-      args <- list(
+      fun_args <- list(
         model,
         ci = ci,
         component = component,
@@ -100,8 +100,8 @@ model_parameters.glmmTMB <- function(model,
         wb_component = wb_component,
         summary = summary
       )
-      args <- c(args, dot_args)
-      params <- do.call(".extract_parameters_generic", args)
+      fun_args <- c(fun_args, dot_args)
+      params <- do.call(".extract_parameters_generic", fun_args)
     }
 
     # add dispersion parameter
@@ -131,7 +131,7 @@ model_parameters.glmmTMB <- function(model,
             if (verbose) {
               insight::format_alert(
                 "Cannot compute standard errors and confidence intervals for sigma parameter.",
-                "Your model may suffer from singularity (see '?lme4::isSingular' and '?performance::check_singularity')."
+                "Your model may suffer from singularity (see '?lme4::isSingular' and '?performance::check_singularity')." # nolint
               )
             }
             c(NA, NA)
@@ -157,7 +157,7 @@ model_parameters.glmmTMB <- function(model,
       params_random <- .extract_random_parameters(model, ci = ci, effects = effects, component = component)
       if (length(random_effects) > 1) {
         insight::format_alert(
-          "Cannot extract confidence intervals for random variance parameters from models with more than one grouping factor."
+          "Cannot extract confidence intervals for random variance parameters from models with more than one grouping factor." # nolint
         )
       }
     } else {
@@ -173,12 +173,12 @@ model_parameters.glmmTMB <- function(model,
       # remove redundant dispersion parameter
       if (isTRUE(dispersion_param) && !is.null(params) && !is.null(params$Component)) {
         disp <- which(params$Component == "dispersion")
-        resid <- which(params_variance$Group == "Residual")
+        res <- which(params_variance$Group == "Residual")
         # check if we have dispersion parameter, and either no sigma
         # or sigma equals dispersion
         if (length(disp) > 0 &&
-          length(resid) > 0 &&
-          isTRUE(all.equal(params_variance$Coefficient[resid],
+          length(res) > 0 &&
+          isTRUE(all.equal(params_variance$Coefficient[res],
             params$Coefficient[disp],
             tolerance = 1e-5
           ))) {
@@ -202,10 +202,10 @@ model_parameters.glmmTMB <- function(model,
     }
 
     # reorder
-    if (!is.null(params_random)) {
-      params <- params[match(colnames(params_random), colnames(params))]
-    } else {
+    if (is.null(params_random)) {
       params <- params[match(colnames(params_variance), colnames(params))]
+    } else {
+      params <- params[match(colnames(params_random), colnames(params))]
     }
   }
 
@@ -466,16 +466,15 @@ simulate_parameters.glmmTMB <- function(model,
                                         ci_method = "quantile",
                                         test = "p-value",
                                         ...) {
-  data <- simulate_model(model, iterations = iterations, ...)
-  out <-
-    .summary_bootstrap(
-      data = data,
-      test = test,
-      centrality = centrality,
-      ci = ci,
-      ci_method = ci_method,
-      ...
-    )
+  sim_data <- simulate_model(model, iterations = iterations, ...)
+  out <- .summary_bootstrap(
+    data = sim_data,
+    test = test,
+    centrality = centrality,
+    ci = ci,
+    ci_method = ci_method,
+    ...
+  )
 
   params <- insight::get_parameters(model, ...)
   if ("Effects" %in% colnames(params) && insight::n_unique(params$Effects) > 1) {
diff --git a/R/methods_hglm.R b/R/methods_hglm.R
index beb24306d..4f237e112 100644
--- a/R/methods_hglm.R
+++ b/R/methods_hglm.R
@@ -223,13 +223,13 @@ p_value.hglm <- function(model,
                          ...) {
   dots <- list(...)
   dots$component <- NULL
-  args <- list(
+  fun_args <- list(
     model,
     dof = dof,
     component = "conditional",
     method = method,
     verbose = verbose
   )
-  args <- c(args, dots)
-  do.call("p_value.default", args)
+  fun_args <- c(fun_args, dots)
+  do.call("p_value.default", fun_args)
 }
diff --git a/R/methods_lme4.R b/R/methods_lme4.R
index 549317ef4..ee1bcd537 100644
--- a/R/methods_lme4.R
+++ b/R/methods_lme4.R
@@ -197,7 +197,7 @@ model_parameters.merMod <- function(model,
         }
       }
     } else {
-      args <- list(
+      fun_args <- list(
         model,
         ci = ci,
         ci_method = ci_method,
@@ -212,8 +212,8 @@ model_parameters.merMod <- function(model,
         vcov = vcov,
         vcov_args = vcov_args
       )
-      args <- c(args, dots)
-      params <- do.call(".extract_parameters_mixed", args)
+      fun_args <- c(fun_args, dots)
+      params <- do.call(".extract_parameters_mixed", fun_args)
     }
 
     params$Effects <- "fixed"
@@ -244,10 +244,10 @@ model_parameters.merMod <- function(model,
     params$Level <- NA
     params$Group <- ""
 
-    if (!is.null(params_random)) {
-      params <- params[match(colnames(params_random), colnames(params))]
-    } else {
+    if (is.null(params_random)) {
       params <- params[match(colnames(params_variance), colnames(params))]
+    } else {
+      params <- params[match(colnames(params_random), colnames(params))]
     }
   }
 
@@ -348,12 +348,12 @@ standard_error.merMod <- function(model,
   }
 
   if (!is.null(vcov) || isTRUE(dots[["robust"]])) {
-    args <- list(model,
+    fun_args <- list(model,
       vcov = vcov,
       vcov_args = vcov_args
     )
-    args <- c(args, dots)
-    out <- do.call("standard_error.default", args)
+    fun_args <- c(fun_args, dots)
+    out <- do.call("standard_error.default", fun_args)
     return(out)
   }
 
diff --git a/R/methods_logistf.R b/R/methods_logistf.R
index 2912c488b..27f47562e 100644
--- a/R/methods_logistf.R
+++ b/R/methods_logistf.R
@@ -49,7 +49,7 @@ p_value.logistf <- function(model, ...) {
   utils::capture.output(s <- summary(model)) # nolint
 
   .data_frame(
-    Parameter = .remove_backticks_from_string(names(s$prob)),
+    Parameter = .remove_backticks_from_string(names(s$coefficients)),
     p = as.vector(s$prob)
   )
 }
diff --git a/R/methods_mice.R b/R/methods_mice.R
index 3f0511b9f..cdf326399 100644
--- a/R/methods_mice.R
+++ b/R/methods_mice.R
@@ -108,7 +108,7 @@ model_parameters.mipo <- function(model,
     merge_by <- "Parameter"
   }
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     merge_by = merge_by,
@@ -119,9 +119,9 @@ model_parameters.mipo <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }
diff --git a/R/methods_nestedLogit.R b/R/methods_nestedLogit.R
index 7cf670ded..90bc86169 100644
--- a/R/methods_nestedLogit.R
+++ b/R/methods_nestedLogit.R
@@ -45,12 +45,12 @@ model_parameters.nestedLogit <- function(model,
   # tell user that profiled CIs don't respect vcov-args
   if (identical(ci_method, "profile") && (!is.null(vcov) || !is.null(vcov_args)) && isTRUE(verbose)) {
     insight::format_alert(
-      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.",
+      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.", # nolint
       "Use `ci_method=\"wald\"` to return confidence intervals based on robust standard errors."
     )
   }
 
-  args <- list(
+  fun_args <- list(
     model = model,
     ci = ci,
     ci_method = ci_method,
@@ -67,8 +67,8 @@ model_parameters.nestedLogit <- function(model,
     vcov = vcov,
     vcov_args = vcov_args
   )
-  args <- c(args, dots)
-  out <- do.call(".model_parameters_generic", args)
+  fun_args <- c(fun_args, dots)
+  out <- do.call(".model_parameters_generic", fun_args)
 
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
@@ -89,19 +89,17 @@ degrees_of_freedom.nestedLogit <- function(model,
     dof <- rep(vapply(model$models, stats::df.residual, numeric(1)), each = nrow(cf))
     if (!is.null(component) && !identical(component, "all")) {
       comp <- intersect(names(dof), component)
-      if (!length(comp)) {
+      if (length(comp)) {
+        dof <- dof[comp]
+      } else {
         if (verbose) {
-          insight::format_alert(
-            paste0(
-              "No matching model found. Possible values for `component` are ",
-              toString(paste0("'", names(model$models), "'")),
-              "."
-            )
-          )
+          insight::format_alert(paste0(
+            "No matching model found. Possible values for `component` are ",
+            toString(paste0("'", names(model$models), "'")),
+            "."
+          ))
         }
         dof <- Inf
-      } else {
-        dof <- dof[comp]
       }
     }
   } else {
@@ -128,8 +126,8 @@ standard_error.nestedLogit <- function(model,
 
   # vcov: function which returns a matrix
   if (is.function(vcov)) {
-    args <- c(list(model), vcov_args, dots)
-    se <- .safe(sqrt(diag(do.call("vcov", args))))
+    fun_args <- c(list(model), vcov_args, dots)
+    se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
   }
 
   # vcov: character (with backward compatibility for `robust = TRUE`)
@@ -182,7 +180,11 @@ p_value.nestedLogit <- function(model,
                                 vcov_args = NULL,
                                 verbose = TRUE,
                                 ...) {
-  if (!is.null(vcov)) {
+  if (is.null(vcov)) {
+    p <- as.vector(as.data.frame(do.call(rbind, lapply(model$models, function(i) {
+      stats::coef(summary(i))
+    })))[, "Pr(>|z|)"])
+  } else {
     p <- p_value.default(
       model,
       dof = dof,
@@ -193,10 +195,6 @@ p_value.nestedLogit <- function(model,
       verbose = verbose,
       ...
     )[["p"]]
-  } else {
-    p <- as.vector(as.data.frame(do.call(rbind, lapply(model$models, function(i) {
-      stats::coef(summary(i))
-    })))[, "Pr(>|z|)"])
   }
 
   params <- insight::get_parameters(model, component = component)
@@ -267,8 +265,8 @@ simulate_model.nestedLogit <- function(model, iterations = 1000, ...) {
 
   out <- lapply(unique(params$Component), function(i) {
     pars <- params[params$Component == i, ]
-    beta <- stats::setNames(pars$Estimate, pars$Parameter)
-    d <- as.data.frame(.mvrnorm(n = iterations, mu = beta, Sigma = varcov[[i]]))
+    betas <- stats::setNames(pars$Estimate, pars$Parameter)
+    d <- as.data.frame(.mvrnorm(n = iterations, mu = betas, Sigma = varcov[[i]]))
     d$Component <- i
     d
   })
@@ -289,10 +287,10 @@ simulate_parameters.nestedLogit <- function(model,
                                             ci_method = "quantile",
                                             test = "p-value",
                                             ...) {
-  data <- simulate_model(model, iterations = iterations, ...)
+  sim_data <- simulate_model(model, iterations = iterations, ...)
 
-  out <- lapply(unique(data$Component), function(i) {
-    pars <- data[data$Component == i, ]
+  out <- lapply(unique(sim_data$Component), function(i) {
+    pars <- sim_data[sim_data$Component == i, ]
     d <- .summary_bootstrap(
       data = pars,
       test = test,
diff --git a/R/methods_plm.R b/R/methods_plm.R
index 109fa53ba..00a120df9 100644
--- a/R/methods_plm.R
+++ b/R/methods_plm.R
@@ -27,8 +27,8 @@ standard_error.plm <- function(model, vcov = NULL, vcov_args = NULL, verbose = T
 
   # vcov: function which returns a matrix
   if (is.function(vcov)) {
-    args <- c(list(model), vcov_args, dots)
-    se <- .safe(sqrt(diag(do.call("vcov", args))))
+    fun_args <- c(list(model), vcov_args, dots)
+    se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
   }
 
   # vcov: character (with backward compatibility for `robust = TRUE`)
diff --git a/R/methods_survey.R b/R/methods_survey.R
index 5b0e4751c..04674bf8f 100644
--- a/R/methods_survey.R
+++ b/R/methods_survey.R
@@ -4,8 +4,6 @@
 model_parameters.svyglm <- function(model,
                                     ci = 0.95,
                                     ci_method = "wald",
-                                    bootstrap = FALSE,
-                                    iterations = 1000,
                                     standardize = NULL,
                                     exponentiate = FALSE,
                                     p_adjust = NULL,
@@ -16,25 +14,32 @@ model_parameters.svyglm <- function(model,
                                     ...) {
   if (insight::n_obs(model) > 1e4 && ci_method == "likelihood") {
     insight::format_alert(
-      "Likelihood confidence intervals may take longer time to compute. Use 'ci_method=\"wald\"' for faster computation of CIs."
+      "Likelihood confidence intervals may take longer time to compute. Use 'ci_method=\"wald\"' for faster computation of CIs." # nolint
     )
   }
 
-  out <- .model_parameters_generic(
-    model = model,
+  # validation check, warn if unsupported argument is used.
+  dot_args <- .check_dots(
+    dots = list(...),
+    not_allowed = c("vcov", "vcov_args", "bootstrap"),
+    class(model)[1],
+    verbose = verbose
+  )
+
+  fun_args <- list(
+    model,
     ci = ci,
     ci_method = ci_method,
-    bootstrap = bootstrap,
-    iterations = iterations,
-    merge_by = "Parameter",
     standardize = standardize,
     exponentiate = exponentiate,
     p_adjust = p_adjust,
     keep_parameters = keep,
     drop_parameters = drop,
     summary = summary,
-    ...
+    verbose = verbose
   )
+  fun_args <- c(fun_args, dot_args)
+  out <- do.call(".model_parameters_generic", fun_args)
 
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
@@ -115,8 +120,8 @@ ci.svyolr <- ci.svyglm
 #' @export
 p_value.svyglm <- function(model, verbose = TRUE, ...) {
   statistic <- insight::get_statistic(model)
-  df <- insight::get_df(model, type = "residual")
-  p <- 2 * stats::pt(-abs(statistic$Statistic), df = df)
+  dof <- insight::get_df(model, type = "residual")
+  p <- 2 * stats::pt(-abs(statistic$Statistic), df = dof)
   .data_frame(
     Parameter = statistic$Parameter,
     p = as.vector(p)
diff --git a/R/utils_model_parameters.R b/R/utils_model_parameters.R
index a59b48d22..eef3a86cc 100644
--- a/R/utils_model_parameters.R
+++ b/R/utils_model_parameters.R
@@ -245,7 +245,7 @@
         "Coefficient"
       )
     }
-  } else if (!is.null(info) && !info$family == "unknown") {
+  } else if (!is.null(info) && info$family != "unknown") {
     if (isTRUE(exponentiate)) {
       if (info$is_exponential && identical(info$link_function, "log")) {
         coef_col <- "Prevalence Ratio"
@@ -348,7 +348,7 @@
   )
 
   # add Group variable
-  if (!is.null(clean_params$Group) && any(nchar(clean_params$Group) > 0)) {
+  if (!is.null(clean_params$Group) && any(nzchar(clean_params$Group, keepNA = TRUE))) {
     params$Group <- .safe(gsub("(.*): (.*)", "\\2", clean_params$Group))
   }
 
@@ -414,10 +414,10 @@
 
 
 .additional_arguments <- function(x, value, default) {
-  args <- attributes(x)$additional_arguments
+  add_args <- attributes(x)$additional_arguments
 
-  if (length(args) > 0 && value %in% names(args)) {
-    out <- args[[value]]
+  if (length(add_args) > 0 && value %in% names(add_args)) {
+    out <- add_args[[value]]
   } else {
     out <- attributes(x)[[value]]
   }
diff --git a/tests/testthat/_snaps/windows/model_parameters.logistf.md b/tests/testthat/_snaps/windows/model_parameters.logistf.md
new file mode 100644
index 000000000..d15d7ac16
--- /dev/null
+++ b/tests/testthat/_snaps/windows/model_parameters.logistf.md
@@ -0,0 +1,63 @@
+# model_parameters.logistf
+
+    Code
+      params
+    Output
+      # Fixed Effects
+      
+      Parameter   | Log-Odds |   SE |         95% CI | Chi2(1) |      p
+      -----------------------------------------------------------------
+      (Intercept) |     0.12 | 0.48 | [-0.82,  1.07] |    0.06 | 0.802 
+      age         |    -1.11 | 0.41 | [-1.97, -0.31] |    7.51 | 0.006 
+      oc          |    -0.07 | 0.43 | [-0.94,  0.79] |    0.02 | 0.875 
+      vic         |     2.27 | 0.54 | [ 1.27,  3.44] |   22.93 | < .001
+      vicl        |    -2.11 | 0.53 | [-3.26, -1.12] |   19.10 | < .001
+      vis         |    -0.79 | 0.41 | [-1.61,  0.02] |    3.70 | 0.054 
+      dia         |     3.10 | 1.51 | [ 0.77,  8.03] |    7.90 | 0.005 
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+
+# model_parameters.flic
+
+    Code
+      params
+    Output
+      # Fixed Effects
+      
+      Parameter   | Log-Odds |   SE |         95% CI | Chi2(1) |      p
+      -----------------------------------------------------------------
+      (Intercept) |     0.13 | 0.28 | [-0.82,  1.08] |    0.85 | 0.358 
+      age         |    -1.11 | 0.29 | [-1.97, -0.31] |    7.51 | 0.006 
+      oc          |    -0.07 | 0.24 | [-0.94,  0.79] |    0.02 | 0.875 
+      vic         |     2.27 | 0.24 | [ 1.27,  3.44] |   22.93 | < .001
+      vicl        |    -2.11 | 0.25 | [-3.26, -1.12] |   19.10 | < .001
+      vis         |    -0.79 | 0.26 | [-1.61,  0.02] |    3.70 | 0.054 
+      dia         |     3.10 | 0.41 | [ 0.77,  8.03] |    7.90 | 0.005 
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+
+# model_parameters.flac
+
+    Code
+      params
+    Output
+      # Fixed Effects
+      
+      Parameter   | Log-Odds |   SE |         95% CI | Chi2(1) |      p
+      -----------------------------------------------------------------
+      (Intercept) |     0.12 | 0.48 | [-0.81,  1.07] |    0.07 | 0.797 
+      age         |    -1.10 | 0.42 | [-1.95, -0.31] |    7.55 | 0.006 
+      oc          |    -0.07 | 0.43 | [-0.93,  0.79] |    0.02 | 0.879 
+      vic         |     2.28 | 0.54 | [ 1.29,  3.43] |   23.37 | < .001
+      vicl        |    -2.11 | 0.53 | [-3.24, -1.13] |   19.45 | < .001
+      vis         |    -0.79 | 0.41 | [-1.60,  0.01] |    3.74 | 0.053 
+      dia         |     3.18 | 1.53 | [ 0.87,  7.99] |    8.54 | 0.003 
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+
diff --git a/tests/testthat/test-model_parameters.logistf.R b/tests/testthat/test-model_parameters.logistf.R
new file mode 100644
index 000000000..f8d4664e8
--- /dev/null
+++ b/tests/testthat/test-model_parameters.logistf.R
@@ -0,0 +1,27 @@
+skip_on_cran()
+
+skip_if_not_installed("logistf")
+skip_if_not_installed("withr")
+
+withr::with_options(
+  list(parameters_exponentiate = FALSE),
+  {
+    data(sex2, package = "logistf")
+    m1 <- logistf::logistf(case ~ age + oc + vic + vicl + vis + dia, data = sex2)
+    m2 <- logistf::flic(m1)
+    m3 <- logistf::flac(m1, data = sex2)
+
+    test_that("model_parameters.logistf", {
+      params <- model_parameters(m1)
+      expect_snapshot(params, variant = "windows")
+    })
+    test_that("model_parameters.flic", {
+      params <- model_parameters(m2)
+      expect_snapshot(params, variant = "windows")
+    })
+    test_that("model_parameters.flac", {
+      params <- model_parameters(m3)
+      expect_snapshot(params, variant = "windows")
+    })
+  }
+)
diff --git a/tests/testthat/test-survey.R b/tests/testthat/test-survey.R
new file mode 100644
index 000000000..71df946cc
--- /dev/null
+++ b/tests/testthat/test-survey.R
@@ -0,0 +1,37 @@
+skip_if_not_installed("withr")
+skip_if_not_installed("survey")
+
+withr::with_environment(
+  new.env(),
+  test_that("model_parameters svytable", {
+    # svychisq is called in model_parameters
+    svychisq <<- survey::svychisq
+
+    data(api, package = "survey")
+    dclus1 <<- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)
+    m <- survey::svytable(~ sch.wide + stype, dclus1)
+    mp <- model_parameters(m)
+    expect_named(mp, c("F", "df", "df_error", "p", "Method"))
+    expect_equal(mp$p, 0.02174746, tolerance = 1e-3)
+  })
+)
+
+withr::with_environment(
+  new.env(),
+  test_that("model_parameters, bootstrap svyglm", {
+    data(api, package = "survey")
+    dstrat <- survey::svydesign(
+      id = ~1,
+      strata = ~stype,
+      weights = ~pw,
+      data = apistrat,
+      fpc = ~fpc
+    )
+
+    model_svyglm <- suppressWarnings(survey::svyglm(sch.wide ~ ell + meals + mobility,
+      design = dstrat,
+      family = binomial(link = "logit")
+    ))
+    expect_message(parameters(model_svyglm, bootstrap = TRUE), regex = "arguments are not supported")
+  })
+)
diff --git a/tests/testthat/test-svytable.R b/tests/testthat/test-svytable.R
deleted file mode 100644
index 8e6792b94..000000000
--- a/tests/testthat/test-svytable.R
+++ /dev/null
@@ -1,12 +0,0 @@
-test_that("model_parameters", {
-  skip_if_not_installed("survey")
-  # svychisq is called in model_parameters
-  svychisq <<- survey::svychisq
-
-  data(api, package = "survey")
-  dclus1 <<- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)
-  m <- survey::svytable(~ sch.wide + stype, dclus1)
-  mp <- model_parameters(m)
-  expect_equal(colnames(mp), c("F", "df", "df_error", "p", "Method"))
-  expect_equal(mp$p, 0.02174746, tolerance = 1e-3)
-})