Improve support for glm.nb

Closes problem with jtools::summ and MASS::glm.nb() #142

NEWS.md

@@ -7,6 +7,11 @@ identity, standard errors were simultaneously being calculated, and the
 user included random effects. This error has been corrected 
 ([#144](https://github.com/jacob-long/jtools/issues/144))
 
+Enhancement:
+
+* `summ()` will now produce model fit statistics for `glm.nb` models 
+([#142](https://github.com/jacob-long/jtools/issues/142)).
+
 # jtools 2.2.2
 
 Bug fix:

R/pR2.R

@@ -21,16 +21,23 @@ pR2Work <- function(llh, llhNull, n, object = NULL, objectNull = NULL) {
   if (!is.null(object)) {
     the_aov <- anova(objectNull, object, test = "Chisq")
 
-    out$chisq <- the_aov$Deviance[2]
-    out$chisq_df <- the_aov$Df[2]
-    out$chisq_p <- the_aov$`Pr(>Chi)`[2]
+    # glm.nb uses different names for the columns
+    if (grepl("Negative Binomial", get_family(object)$family)) {
+      out$chisq <- the_aov$`LR stat.`[2]
+      out$chisq_df <- the_aov$`Resid. df`[2]
+      out$chisq_p <- the_aov$`Pr(Chi)`[2]
+    } else {
+      out$chisq <- the_aov$Deviance[2]
+      out$chisq_df <- the_aov$Df[2]
+      out$chisq_p <- the_aov$`Pr(>Chi)`[2]
+    }
   }
 
   out
 }
 
 pR2 <- function(object) {
-  
+
   llh <- getLL(object)
 
   if (get_family(object)$family %in% c("quasibinomial","quasipoisson")) {
@@ -75,7 +82,11 @@ pR2 <- function(object) {
   if ("start" %in% names(call)) {
     call$start <- NULL
   } 
-  call$family <- get_family(object)
+  # Can't attach the family object from glm.nb objects because of 
+  # the theta parameter being estimated based on the model spec.
+  if (!grepl("Negative Binomial", get_family(object)$family)) {
+    call$family <- get_family(object)
+  }
   # Update the model
   objectNull <- try(eval(call))
   if ("try-error" %in% class(objectNull)) {

tests/testthat/test-jsumm.R

@@ -112,6 +112,19 @@ test_that("summ: knit_print works", {
   }
 })
 
+if (requireNamespace("MASS")) {
+  # Negative binomial test
+  library(MASS, quietly = TRUE)
+  data(quine)
+  fitnb <- MASS::glm.nb(Days ~ Sex/(Age + Eth*Lrn), data = quine)
+  test_that("summ: negative binomial works",
+    expect_is(summ(fitnb), "summ.glm")
+  )
+  test_that("summ: negative binomial pR2 works",
+    expect_is(attr(summ(fitnb), "chisq")$df, "numeric")
+  )
+}
+
 options("summ-stars" = FALSE)
 
 # Test handling of singular models