Now tidy_add_n() works with multinomial models when y is not code…

…d as a factor

fix #109

NEWS.md

@@ -4,6 +4,8 @@
 
 - Better identification of term labels for interaction terms using sum 
   contrasts (#108)
+- Now `tidy_add_n()` works with multinomial models when `y` is not coded as
+  a factor (#109)
 
 # broom.helpers 1.2.0
 

R/model_get_n.R

@@ -163,6 +163,7 @@ model_get_n.multinom <- function(model) {
 
   w <- model %>% model_get_weights()
   y <- model %>% model_get_response()
+  if (!is.factor(y)) y <- factor(y)
 
   n <- purrr::map_df(
     levels(y)[-1],

tests/testthat/test-add_n.R

@@ -202,6 +202,14 @@ test_that("tidy_add_n() works with nnet::multinom", {
     res$n_event,
     c(57, 21, 16, 8, 57, 57, 58, 12, 18, 12, 58, 58)
   )
+
+  # when y is not coded as a factor
+  mod <- multinom(race ~ age + lwt + bwt, data = MASS::birthwt)
+  expect_error(
+    mod %>% tidy_and_attach() %>% tidy_add_n(),
+    NA
+  )
+
 })
 
 test_that("tidy_add_n() works with survey::svyglm", {

tests/testthat/test-model_get_n.R

@@ -256,6 +256,10 @@ test_that("model_get_n() works with nnet::multinom", {
     res$n_event,
     c(57, 16, 8, 12, 57, 57, 21, 58, 18, 12, 16, 58, 58, 12)
   )
+
+  # when y is not coded as a factor
+  mod <- multinom(race ~ age + lwt + bwt, data = MASS::birthwt)
+  expect_true(mod %>% model_get_n() %>% nrow() > 0)
 })
 
 test_that("model_get_n() works with survey::svyglm", {