update

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: performance
 Title: Assessment of Regression Models Performance
-Version: 0.12.0.3
+Version: 0.12.0.4
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",

NEWS.md

@@ -11,6 +11,9 @@
   approximation method for the distribution-specific (residual) variance. See
   Nakagawa et al. 2017 for details.
 
+* `icc()` and `r2_nakagawa()` get a `model_component` argument indicating the 
+  component for zero-inflation or hurdle models.
+
 # performance 0.12.0
 
 ## Breaking

R/icc.R

@@ -178,6 +178,7 @@ icc <- function(model,
                 ci_method = NULL,
                 null_model = NULL,
                 approximation = "lognormal",
+                model_component = NULL,
                 verbose = TRUE,
                 ...) {
   # special handling for smicd::semLme()
@@ -210,7 +211,8 @@ icc <- function(model,
     model,
     tolerance = tolerance,
     null_model = null_model,
-    approximation = approximation
+    approximation = approximation,
+    model_component = model_component
   )
 
   # return if ICC couldn't be computed
@@ -545,6 +547,7 @@ print.icc_decomposed <- function(x, digits = 2, ...) {
                                  name_fun = "icc()",
                                  name_full = "ICC",
                                  null_model = NULL,
+                                 model_component = NULL,
                                  approximation = "lognormal",
                                  verbose = TRUE) {
   vars <- tryCatch(
@@ -554,6 +557,7 @@ print.icc_decomposed <- function(x, digits = 2, ...) {
       tolerance = tolerance,
       null_model = null_model,
       approximation = approximation,
+      model_component = model_component,
       verbose = verbose
     ),
     error = function(e) {

R/r2_nakagawa.R

@@ -85,6 +85,7 @@ r2_nakagawa <- function(model,
                         ci_method = NULL,
                         null_model = NULL,
                         approximation = "lognormal",
+                        model_component = NULL,
                         verbose = TRUE,
                         ...) {
   # calculate random effect variances
@@ -95,7 +96,8 @@ r2_nakagawa <- function(model,
     null_model = null_model,
     approximation = approximation,
     name_fun = "r2()",
-    name_full = "r-squared"
+    name_full = "r-squared",
+    model_component = model_component
   )
 
   # return if R2 couldn't be computed