avoid loaded term

R/check_distribution.R

@@ -191,7 +191,7 @@ check_distribution.numeric <- function(model) {
 # utilities -----------------------------
 
 .extract_features <- function(x) {
-  # sanity check, remove missings
+  # validation check, remove missings
   x <- x[!is.na(x)]
 
   data.frame(

R/check_factorstructure.R

@@ -120,7 +120,7 @@ check_factorstructure <- function(x, n = NULL, ...) {
 #' @rdname check_factorstructure
 #' @export
 check_kmo <- function(x, n = NULL, ...) {
-  out <- .check_factor_structure_sanity(x, n, ...)
+  out <- .validate_factor_structure(x, n, ...)
 
   Q <- solve(out$r)
 
@@ -177,7 +177,7 @@ check_kmo <- function(x, n = NULL, ...) {
 #' @rdname check_factorstructure
 #' @export
 check_sphericity_bartlett <- function(x, n = NULL, ...) {
-  out <- .check_factor_structure_sanity(x, n, ...)
+  out <- .validate_factor_structure(x, n, ...)
 
   p <- dim(out$r)[2]
 
@@ -221,15 +221,14 @@ check_sphericity_bartlett <- function(x, n = NULL, ...) {
 # Helpers -----------------------------------------------------------------
 
 #' @keywords internal
-.check_factor_structure_sanity <- function(x, n = NULL, ...) {
+.validate_factor_structure <- function(x, n = NULL, ...) {
   if (is.null(n)) {
     r <- stats::cor(x, use = "pairwise.complete.obs", ...)
     n <- nrow(x)
   } else {
     r <- x
   }
 
-  # Sanity check
   if (nrow(r) != ncol(r)) {
     insight::format_error("The correlation matrix is not square.")
   }

R/check_model_diagnostics.R

@@ -67,7 +67,7 @@
     fitted_ <- stats::fitted(model)
   }
 
-  # sanity check, sometimes either residuals or fitted can contain NA, see #488
+  # validation check, sometimes either residuals or fitted can contain NA, see #488
   if (anyNA(res_) || anyNA(fitted_)) {
     # drop NA and make sure both fitted and residuals match
     non_na <- !is.na(fitted_) & !is.na(res_)

R/check_outliers.R

@@ -1808,7 +1808,7 @@ check_outliers.metabin <- check_outliers.metagen
 
   # Get results
   cutoff <- .safe(outliers@ics.dist.cutoff)
-  # sanity check
+  # validation check
   if (is.null(cutoff)) {
     insight::print_color("Could not detect cut-off for outliers.\n", "red")
     return(NULL)

R/check_predictions.R

@@ -193,7 +193,7 @@ pp_check.lm <- function(object,
   # else, proceed as usual
   out <- .safe(stats::simulate(object, nsim = iterations, re.form = re_formula, ...))
 
-  # sanity check, for mixed models, where re.form = NULL (default) might fail
+  # validation check, for mixed models, where re.form = NULL (default) might fail
   out <- .check_re_formula(out, object, iterations, re_formula, verbose, ...)
 
   # save information about model
@@ -270,7 +270,7 @@ pp_check.glm <- function(object,
     }
   )
 
-  # sanity check, for mixed models, where re.form = NULL (default) might fail
+  # validation check, for mixed models, where re.form = NULL (default) might fail
   out <- .check_re_formula(out, object, iterations, re_formula, verbose, ...)
 
   if (is.null(out)) {
@@ -444,7 +444,7 @@ plot.performance_pp_check <- function(x, ...) {
 
 
 .check_re_formula <- function(out, object, iterations, re_formula, verbose, ...) {
-  # sanity check, for mixed models, where re.form = NULL (default) might fail
+  # validation check, for mixed models, where re.form = NULL (default) might fail
   if (is.null(out) && insight::is_mixed_model(object) && !isTRUE(is.na(re_formula))) {
     if (verbose) {
       insight::format_warning(

R/check_sphericity.R

@@ -67,7 +67,7 @@ check_sphericity.Anova.mlm <- function(x, ...) {
 
   p.val <- test[, 2]
 
-  # sanity check
+  # validation check
   if (is.null(p.val)) {
     p.val <- 1
   }

R/icc.R

@@ -267,7 +267,7 @@ icc <- function(model,
         # CI for adjusted ICC
         icc_ci_adjusted <- as.vector(result$t[, 1])
         icc_ci_adjusted <- icc_ci_adjusted[!is.na(icc_ci_adjusted)]
-        # sanity check
+        # validation check
         if (length(icc_ci_adjusted) > 0) {
           icc_ci_adjusted <- bayestestR::eti(icc_ci_adjusted, ci = ci)
         } else {
@@ -276,7 +276,7 @@ icc <- function(model,
         # CI for unadjusted ICC
         icc_ci_unadjusted <- as.vector(result$t[, 2])
         icc_ci_unadjusted <- icc_ci_unadjusted[!is.na(icc_ci_unadjusted)]
-        # sanity check
+        # validation check
         if (length(icc_ci_unadjusted) > 0) {
           icc_ci_unadjusted <- bayestestR::eti(icc_ci_unadjusted, ci = ci)
         } else {

R/r2_nakagawa.R

@@ -136,7 +136,7 @@ r2_nakagawa <- function(model,
         # CI for marginal R2
         r2_ci_marginal <- as.vector(result$t[, 1])
         r2_ci_marginal <- r2_ci_marginal[!is.na(r2_ci_marginal)]
-        # sanity check
+        # validation check
         if (length(r2_ci_marginal) > 0) {
           r2_ci_marginal <- bayestestR::eti(r2_ci_marginal, ci = ci)
         } else {
@@ -146,7 +146,7 @@ r2_nakagawa <- function(model,
         # CI for unadjusted R2
         r2_ci_conditional <- as.vector(result$t[, 2])
         r2_ci_conditional <- r2_ci_conditional[!is.na(r2_ci_conditional)]
-        # sanity check
+        # validation check
         if (length(r2_ci_conditional) > 0) {
           r2_ci_conditional <- bayestestR::eti(r2_ci_conditional, ci = ci)
         } else {

R/test_bf.R

@@ -12,7 +12,7 @@ test_bf.default <- function(..., reference = 1, text_length = NULL) {
   objects <- insight::ellipsis_info(..., only_models = TRUE)
   names(objects) <- match.call(expand.dots = FALSE)$`...`
 
-  # Sanity checks (will throw error if non-valid objects)
+  # validation checks (will throw error if non-valid objects)
   .test_performance_checks(objects, multiple = FALSE)
 
   if (length(objects) == 1 && isTRUE(insight::is_model(objects))) {

R/test_likelihoodratio.R

@@ -24,7 +24,7 @@ test_likelihoodratio.default <- function(..., estimator = "OLS", verbose = TRUE)
   # Attribute class to list
   objects <- insight::ellipsis_info(..., only_models = TRUE)
 
-  # Sanity checks (will throw error if non-valid objects)
+  # validation checks (will throw error if non-valid objects)
   objects <- .test_performance_checks(objects, verbose = verbose)
 
   # different default when mixed model or glm is included

R/test_performance.R

@@ -238,7 +238,7 @@ test_performance.default <- function(..., reference = 1, include_formula = FALSE
   # Attribute class to list and get names from the global environment
   objects <- insight::ellipsis_info(..., only_models = TRUE)
 
-  # Sanity checks (will throw error if non-valid objects)
+  # validation checks (will throw error if non-valid objects)
   objects <- .test_performance_checks(objects, verbose = verbose)
 
   # ensure proper object names

R/test_vuong.R

@@ -10,7 +10,7 @@ test_vuong.default <- function(..., reference = 1, verbose = TRUE) {
   # Attribute class to list and get names from the global environment
   objects <- insight::ellipsis_info(..., only_models = TRUE)
 
-  # Sanity checks (will throw error if non-valid objects)
+  # validation checks (will throw error if non-valid objects)
   objects <- .test_performance_checks(objects, verbose = verbose)
 
   # ensure proper object names

R/test_wald.R

@@ -10,7 +10,7 @@ test_wald.default <- function(..., verbose = TRUE) {
   # Attribute class to list and get names from the global environment
   objects <- insight::ellipsis_info(..., only_models = TRUE)
 
-  # Sanity checks (will throw error if non-valid objects)
+  # validation checks (will throw error if non-valid objects)
   objects <- .test_performance_checks(objects, verbose = verbose)
 
   # ensure proper object names