format_alerts

R/bayesfactor_parameters.R

@@ -199,7 +199,7 @@ bayesfactor_pointnull <- function(posterior,
                                   verbose = TRUE,
                                   ...) {
   if (length(null) > 1 && verbose) {
-    message("'null' is a range - computing a ROPE based Bayes factor.")
+    insight::format_alert("`null` is a range - computing a ROPE based Bayes factor.")
   }
 
   bayesfactor_parameters(

R/describe_posterior.R

@@ -499,8 +499,6 @@ describe_posterior.default <- function(posteriors, ...) {
     row.names(out) <- NULL
   }
 
-
-
   # Prepare output
   attr(out, "ci_method") <- ci_method
   out

R/mediation.R

@@ -179,7 +179,7 @@ mediation.stanmvreg <- function(model, treatment, mediator, response = NULL, cen
   # check for binary response. In this case, user should rescale variables
   modelinfo <- insight::model_info(model)
   if (any(sapply(modelinfo, function(i) i$is_binomial, simplify = TRUE))) {
-    message("One of moderator or outcome is binary, so direct and indirect effects may be on different scales. Consider rescaling model predictors, e.g. with `effectsize::standardize()`.")
+    insight::format_alert("One of moderator or outcome is binary, so direct and indirect effects may be on different scales. Consider rescaling model predictors, e.g. with `effectsize::standardize()`.")
   }
 
   # model responses
@@ -355,7 +355,7 @@ print.bayestestR_mediation <- function(x, digits = 3, ...) {
   )
 
   if (any(prop_mediated_ori$Estimate < 0)) {
-    message("\nDirect and indirect effects have opposite directions. The proportion mediated is not meaningful.")
+    insight::format_alert("\nDirect and indirect effects have opposite directions. The proportion mediated is not meaningful.")
   }
 }
 

R/plot.R

@@ -46,42 +46,49 @@ plot.bayestestR_eti <- function(x, ...) {
   NextMethod()
 }
 
+
 #' @export
 plot.bayestestR_si <- function(x, ...) {
   insight::check_if_installed("see", "to plot support intervals")
   NextMethod()
 }
 
+
 #' @export
 plot.bayesfactor_parameters <- function(x, ...) {
   insight::check_if_installed("see", "to plot Savage-Dickey Bayes factor")
   NextMethod()
 }
 
+
 #' @export
 plot.bayesfactor_models <- function(x, ...) {
   insight::check_if_installed("see", "to plot models' Bayes factors")
   NextMethod()
 }
 
+
 #' @export
 plot.estimate_density <- function(x, ...) {
   insight::check_if_installed("see", "to plot densities")
   NextMethod()
 }
 
+
 #' @export
 plot.estimate_density_df <- function(x, ...) {
   insight::check_if_installed("see", "to plot models' densities")
   NextMethod()
 }
 
+
 #' @export
 plot.p_significance <- function(x, ...) {
   insight::check_if_installed("see", "to plot practical significance")
   NextMethod()
 }
 
+
 #' @export
 plot.describe_posterior <- function(x, stack = FALSE, ...) {
   insight::check_if_installed("see", "to plot posterior samples")
@@ -91,6 +98,6 @@ plot.describe_posterior <- function(x, stack = FALSE, ...) {
     graphics::plot(estimate_density(model), stack = stack, ...) +
       ggplot2::labs(title = "Posterior Samples", x = NULL, y = NULL)
   } else {
-    warning(insight::format_message("Could not find model-object. Try ' plot(estimate_density(model))' instead."), call. = FALSE)
+    insight::format_warning("Could not find model-object. Try `plot(estimate_density(model))` instead.")
   }
 }

R/simulate_priors.R

@@ -127,7 +127,7 @@ simulate_prior.bcplm <- function(model, n = 1000, verbose = TRUE, ...) {
   }
 
   if (sim_error_msg && verbose) {
-    warning(paste0("Can't simulate priors from a ", prior$Distribution, " distribution."), call. = FALSE)
+    insight::format_warning(paste0("Can't simulate priors from a ", prior$Distribution, " distribution."))
   }
 
   simulated$.bamboozled <- NULL

R/unupdate.R

@@ -34,7 +34,7 @@ unupdate.stanreg <- function(model, verbose = TRUE, ...) {
   }
 
   if (verbose) {
-    message("Sampling priors, please wait...")
+    insight::format_alert("Sampling priors, please wait...")
   }
 
   prior_dists <- sapply(rstanarm::prior_summary(model), `[[`, "dist")
@@ -63,7 +63,7 @@ unupdate.brmsfit <- function(model, verbose = TRUE, ...) {
   }
 
   if (verbose) {
-    message("Sampling priors, please wait...")
+    insight::format_alert("Sampling priors, please wait...")
   }
 
   utils::capture.output({
@@ -99,7 +99,7 @@ unupdate.brmsfit_multiple <- function(model,
   }
 
   if (verbose) {
-    message("Sampling priors, please wait...")
+    insight::format_alert("Sampling priors, please wait...")
   }
 
   utils::capture.output({model_prior <-
@@ -138,7 +138,7 @@ unupdate.blavaan <- function(model, verbose = TRUE, ...) {
   }
 
   if (verbose) {
-    message("Sampling priors, please wait...")
+    insight::format_alert("Sampling priors, please wait...")
   }
 
   cl$prisamp <- TRUE

R/utils.R

@@ -61,24 +61,34 @@
     return(temp)
   }
   if (isTRUE(is_stan_mv)) {
+    # for models with multiple responses, we create a separate response column
     temp$Response <- gsub("(b\\[)*(.*)\\|(.*)", "\\2", temp$Parameter)
+    # from the parameter names, we can now remove the name of the respone variables
     for (i in unique(temp$Response)) {
       temp$Parameter <- gsub(sprintf("%s|", i), "", temp$Parameter, fixed = TRUE)
     }
     merge_by <- c("Parameter", "Effects", "Component", "Response")
     remove_cols <- c("Group", "Cleaned_Parameter", "Function", ".roworder")
   } else if (isTRUE(is_brms_mv)) {
+    # for models with multiple responses, we create a separate response column
     temp$Response <- gsub("(.*)_(.*)_(.*)", "\\2", temp$Parameter)
-    # temp$Parameter <- gsub("(.*)_(.*)_(.*)", "\\1_\\3", temp$Parameter)
     merge_by <- c("Parameter", "Effects", "Component", "Response")
     remove_cols <- c("Group", "Cleaned_Parameter", "Function", ".roworder")
   } else {
+    # By default, we only merge by these three columns
     merge_by <- c("Parameter", "Effects", "Component")
     remove_cols <- c("Group", "Cleaned_Parameter", "Response", "Function", ".roworder")
   }
+
+  # in "temp", we have the data frame from the related functions (like
+  # `point_estimate()`, `ci()`  etc.). "cleaned_parameters" is a data frame
+  # only with original parameter names, model components and "cleaned"
+  # parameter names (retrieved from `insight::clean_parameters()`).
+
   merge_by <- intersect(merge_by, colnames(temp))
   temp$.roworder <- seq_len(nrow(temp))
   out <- merge(x = temp, y = cleaned_parameters, by = merge_by, all.x = TRUE)
+
   # hope this works for stanmvreg...
   if ((isTRUE(is_stan_mv) || isTRUE(is_brms_mv)) && all(is.na(out$Effects)) && all(is.na(out$Component))) {
     out$Effects <- cleaned_parameters$Effects[seq_len(nrow(out))]

R/utils_bayesfactor.R

@@ -70,10 +70,7 @@
 
   if (is.null(prior)) {
     prior <- posterior
-    warning(
-      "Prior not specified! ",
-      "Please provide the original model to get meaningful results."
-    )
+    insight::format_warning("Prior not specified! Please provide the original model to get meaningful results.")
   }
 
 
@@ -132,10 +129,7 @@
                                                   verbose = TRUE) {
   if (is.null(prior)) {
     prior <- posterior
-    warning(
-      "Prior not specified! ",
-      "Please provide the original model to get meaningful results."
-    )
+    insight::format_warning("Prior not specified! Please provide the original model to get meaningful results.")
   }
 
   if (!inherits(prior, "emm_list")) {

R/utils_check_collinearity.R

@@ -45,14 +45,26 @@
         results <- results[results$corr > threshold & results$corr <= 0.9, ]
         if (nrow(results) > 0) {
           where <- paste0("between ", toString(paste0(results$where, " (r = ", round(results$corr, 2), ")")), "")
-          message("Possible multicollinearity ", where, ". This might lead to inappropriate results. See 'Details' in '?", method, "'.")
+          insight::format_alert(paste0(
+            "Possible multicollinearity ",
+            where,
+            ". This might lead to inappropriate results. See 'Details' in '?",
+            method,
+            "'."
+          ))
         }
 
         # Filter by second threshold
         results <- results[results$corr > 0.9, ]
         if (nrow(results) > 0) {
           where <- paste0("between ", toString(paste0(results$where, " (r = ", round(results$corr, 2), ")")), "")
-          warning("Probable multicollinearity ", where, ". This might lead to inappropriate results. See 'Details' in '?", method, "'.", call. = FALSE)
+          insight::format_warning(paste0(
+            "Probable multicollinearity ",
+            where,
+            ". This might lead to inappropriate results. See 'Details' in '?",
+            method,
+            "'."
+          ))
         }
       }
     }