Merge branch 'main' of https://github.com/easystats/parameters

R/1_model_parameters.R

@@ -475,10 +475,10 @@ model_parameters.default <- function(model,
                                      vcov = NULL,
                                      vcov_args = NULL,
                                      ...) {
-  # sanity check for inputs
+  # validation check for inputs
   .is_model_valid(model)
 
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   # unsupported arguments will be removed from the argument list.
   dots <- .check_dots(
     dots = list(...),

R/ci_generic.R

@@ -91,7 +91,7 @@
   # for polr, we need to fix parameter names
   params$Parameter <- gsub("Intercept: ", "", params$Parameter, fixed = TRUE)
 
-  # sanity check...
+  # validation check...
   if (is.null(method)) {
     method <- "wald"
   }

R/cluster_analysis.R

@@ -148,12 +148,12 @@ cluster_analysis <- function(x,
     x <- as.data.frame(x)
   }
 
-  # sanity check - needs data frame
+  # validation check - needs data frame
   if (!is.data.frame(x)) {
     insight::format_error("`x` needs to be a data frame.")
   }
 
-  # sanity check - need at least two columns
+  # validation check - need at least two columns
   if (ncol(x) < 2) {
     insight::format_error("At least two variables required to compute a cluster analysis.")
   }

R/cluster_meta.R

@@ -77,7 +77,7 @@ cluster_meta <- function(list_of_clusters, rownames = NULL, ...) {
     x[[name]] <- solution
   }
 
-  # Sanity check
+  # validation check
   if (length(unique(lengths(x))) != 1) {
     insight::format_error("The clustering solutions are not of equal lengths.")
   }

R/equivalence_test.R

@@ -315,7 +315,7 @@ equivalence_test.ggeffects <- function(x,
 
   x <- .get_ggeffects_model(x)
 
-  # sanity check rope range
+  # validation check rope range
   rule <- match.arg(tolower(rule), choices = c("bayes", "classic", "cet"))
   range <- .check_rope_range(x, range, verbose)
 

R/format_parameters.R

@@ -367,7 +367,7 @@ format_parameters.parameters_model <- function(model, ...) {
     model <- .get_object(params)
   }
 
-  # sanity check
+  # validation check
   if (!is.null(model) && insight::is_regression_model(model) && !is.data.frame(model)) {
     # get data, but exclude response - we have no need for that label
     mf <- insight::get_data(model, source = "mf", verbose = FALSE)

R/methods_BayesFactor.R

@@ -196,7 +196,7 @@ model_parameters.BFBayesFactor <- function(model,
 
   out <- datawizard::remove_empty(out)
 
-  # sanity check: make sure BF column still exists,
+  # validation check: make sure BF column still exists,
   # see https://github.com/easystats/correlation/issues/269
   if (is.null(out$BF)) {
     out$BF <- NA

R/methods_betareg.R

@@ -15,7 +15,7 @@ model_parameters.betareg <- function(model,
                                      drop = NULL,
                                      verbose = TRUE,
                                      ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -62,7 +62,7 @@ ci.betareg <- function(x,
                        component = "all",
                        verbose = TRUE,
                        ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -81,7 +81,7 @@ standard_error.betareg <- function(model,
                                    component = "all",
                                    verbose = TRUE,
                                    ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -116,7 +116,7 @@ p_value.betareg <- function(model,
                             component = c("all", "conditional", "precision"),
                             verbose = TRUE,
                             ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),

R/methods_brglm2.R

@@ -19,7 +19,7 @@ model_parameters.bracl <- function(model,
                                    drop = NULL,
                                    verbose = TRUE,
                                    ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -70,7 +70,7 @@ model_parameters.bracl <- function(model,
 
 #' @export
 ci.bracl <- function(x, ci = 0.95, method = NULL, verbose = TRUE, ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -90,7 +90,7 @@ ci.bracl <- function(x, ci = 0.95, method = NULL, verbose = TRUE, ...) {
 
 #' @export
 standard_error.bracl <- function(model, verbose = TRUE, ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -115,7 +115,7 @@ standard_error.bracl <- function(model, verbose = TRUE, ...) {
 
 #' @export
 p_value.bracl <- function(model, verbose = TRUE, ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),

R/methods_cgam.R

@@ -43,7 +43,7 @@ model_parameters.cgam <- function(model,
                                   drop = NULL,
                                   verbose = TRUE,
                                   ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args", "component"),

R/methods_glmmTMB.R

@@ -28,7 +28,7 @@ model_parameters.glmmTMB <- function(model,
                                      ...) {
   insight::check_if_installed("glmmTMB")
 
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),
@@ -268,7 +268,7 @@ ci.glmmTMB <- function(x,
     return(NULL)
   }
 
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),

R/methods_hglm.R

@@ -115,7 +115,7 @@ standard_error.hglm <- function(model,
     return(NULL)
   }
 
-  # sanity check, make sure we have a dispersion component
+  # validation check, make sure we have a dispersion component
   if (component == "all" && is.null(f$dispersion)) {
     compomnent <- "conditional"
   }

R/methods_mice.R

@@ -92,7 +92,7 @@ model_parameters.mipo <- function(model,
                                   drop = NULL,
                                   verbose = TRUE,
                                   ...) {
-  # sanity check, warn if unsupported argument is used.
+  # validation check, warn if unsupported argument is used.
   dot_args <- .check_dots(
     dots = list(...),
     not_allowed = c("vcov", "vcov_args"),

R/pool_parameters.R

@@ -186,7 +186,7 @@ pool_parameters <- function(x,
       df_column <- grep("(\\bdf\\b|\\bdf_error\\b)", colnames(i), value = TRUE)[1]
       if (length(df_column)) {
         pooled_df <- .barnad_rubin(m = nrow(i), b = stats::var(i$Coefficient), t = tmp, dfcom = unique(i[[df_column]]))
-        # sanity check length
+        # validation check length
         if (length(pooled_df) > 1 && length(pooled_se) == 1) {
           pooled_df <- round(mean(pooled_df, na.rm = TRUE))
         }

R/standardize_info.R

@@ -55,15 +55,15 @@ standardize_info.default <- function(model,
   data <- insight::get_data(model, source = "mf", verbose = FALSE)
   wgts <- insight::get_weights(model, na_rm = TRUE)
 
-  # Sanity Check for ZI
+  # validation check for ZI
   if (mi$is_zero_inflated && verbose) {
     insight::format_alert(
       "Non-refit parameter standardization is ignoring the zero-inflation component."
     )
     # would need to also get the binomial model matrix...
   }
 
-  # Sanity Check for glmmTMB with dispersion
+  # validation check for glmmTMB with dispersion
   if (length(params) != nrow(types)) {
     types <- types[types$Parameter %in% params, ]
   }

R/standardize_parameters.R

@@ -550,7 +550,7 @@ print_html.parameters_standardized <- function(x, digits = 2, ...) {
                                             exponentiate,
                                             include_response,
                                             verbose) {
-  # Sanity Check for "pseudo"
+  # validation check for "pseudo"
   method <- .should_pseudo(method, model, mi)
 
   method <- .cant_smart_or_posthoc(method, model, mi, pars$Parameter)

R/standardize_posteriors.R

@@ -51,7 +51,7 @@ standardise_posteriors <- standardize_posteriors
 
 #' @keywords internal
 .standardize_posteriors_posthoc <- function(pars, method, model, mi, robust, two_sd, include_response, verbose) {
-  # Sanity Check for "pseudo"
+  # validation check for "pseudo"
   method <- .should_pseudo(method, model)
 
   method <- .cant_smart_or_posthoc(method, model, mi, pars$Parameter)

R/utils_format.R

@@ -666,7 +666,7 @@
       i
     })
 
-    # sanity check - check if all parameter names in the
+    # validation check - check if all parameter names in the
     # group list are spelled correctly
     misspelled <- vapply(group_rows, anyNA, TRUE)
 
@@ -926,7 +926,7 @@
   # make sure we have correct sorting here...
   tables <- split(x, f = split_by)
 
-  # sanity check - only preserve tables with any data in data frames
+  # validation check - only preserve tables with any data in data frames
   tables <- tables[vapply(tables, nrow, numeric(1)) > 0]
 
 

WIP/extract_random_variances.R

@@ -882,7 +882,7 @@
         # anything missing? (i.e. correlated slope-intercept slopes)
         missig_rnd_slope <- setdiff(names(out), names(rndslopes))
         if (length(missig_rnd_slope)) {
-          # sanity check
+          # validation check
           to_remove <- c()
           for (j in seq_along(out)) {
             # identical random slopes might have different names, so