lintr

R/check_model_diagnostics.R

@@ -85,9 +85,9 @@
 
 # prepare data for random effects QQ plot ----------------------------------
 
-.diag_reqq <- function(model, level = 0.95, model_info, verbose = TRUE) {
+.diag_reqq <- function(model, level = 0.95, model_info = NULL, verbose = TRUE) {
   # check if we have mixed model
-  if (!model_info$is_mixed) {
+  if (is.null(model_info) || !model_info$is_mixed) {
     return(NULL)
   }
 
@@ -156,7 +156,10 @@
   r <- try(as.numeric(stats::residuals(model)), silent = TRUE)
 
   if (inherits(r, "try-error")) {
-    insight::format_alert(sprintf("Non-normality of residuals could not be computed. Cannot extract residuals from objects of class '%s'.", class(model)[1]))
+    insight::format_alert(sprintf(
+      "Non-normality of residuals could not be computed. Cannot extract residuals from objects of class '%s'.",
+      class(model)[1]
+    ))
     return(NULL)
   }
 
@@ -223,7 +226,10 @@
 
   if (is.null(ncv)) {
     if (verbose) {
-      insight::format_alert(sprintf("Non-constant error variance could not be computed. Cannot extract residuals from objects of class '%s'.", class(model)[1]))
+      insight::format_alert(sprintf(
+        "Non-constant error variance could not be computed. Cannot extract residuals from objects of class '%s'.",
+        class(model)[1]
+      ))
     }
     return(NULL)
   }
@@ -264,7 +270,10 @@
 
   if (is.null(r)) {
     if (verbose) {
-      insight::format_alert(sprintf("Homogeneity of variance could not be computed. Cannot extract residual variance from objects of class '%s'.", class(model)[1]))
+      insight::format_alert(sprintf(
+        "Homogeneity of variance could not be computed. Cannot extract residual variance from objects of class '%s'.",
+        class(model)[1]
+      ))
     }
     return(NULL)
   }
@@ -327,7 +336,7 @@
     }
     d$Prob <- stats::predict(model, type = ptype)
     d$Disp <- insight::get_sigma(model)
-    d$V <- d$Predicted * (1 + d$Predicted / d$Disp) * (1 - d$Prob) * (1 + d$Predicted * (1 + d$Predicted / d$Disp) * d$Prob)
+    d$V <- d$Predicted * (1 + d$Predicted / d$Disp) * (1 - d$Prob) * (1 + d$Predicted * (1 + d$Predicted / d$Disp) * d$Prob) # nolint
     d$StdRes <- insight::get_residuals(model, type = "pearson")
   }
 
@@ -343,7 +352,7 @@
     }
     d$Prob <- stats::predict(model, type = ptype)
     d$Disp <- stats::predict(model, type = "disp")
-    d$V <- d$Predicted * (1 + d$Predicted / d$Disp) * (1 - d$Prob) * (1 + d$Predicted * (1 + d$Predicted / d$Disp) * d$Prob)
+    d$V <- d$Predicted * (1 + d$Predicted / d$Disp) * (1 - d$Prob) * (1 + d$Predicted * (1 + d$Predicted / d$Disp) * d$Prob) # nolint
     d$StdRes <- insight::get_residuals(model, type = "pearson")
   }