include more information for glance.lm with one predictor and 0-int…

…ercept (#1209)



---------

Co-authored-by: simonpcouch <simonpatrickcouch@gmail.com>

NEWS.md

@@ -1,5 +1,8 @@
 # broom (development version)
 
+* `glance.lm()` now returns non-`NA` values for `statistic`, `p.value`, and `df` 
+  for models fitted with a single predictor and no intercept (@jrob95, #1209).
+
 # broom 1.0.6
 
 ## New Features

R/stats-lm-tidiers.R

@@ -210,7 +210,7 @@ glance.lm <- function(x, ...) {
 
   # check whether the model was fitted with only an intercept, in which
   # case drop the fstatistic related columns
-  int_only <- nrow(summary(x)$coefficients) == 1
+  int_only <- nrow(summary(x)$coefficients) == 1  & "(Intercept)" %in% row.names(summary(x)$coefficients)
 
   with(
     summary(x),

tests/testthat/test-stats-lm.R

@@ -13,6 +13,7 @@ test_that("lm tidier arguments", {
 fit <- lm(mpg ~ wt, mtcars)
 fit2 <- lm(mpg ~ wt + log(disp), mtcars)
 fit3 <- lm(mpg ~ 1, mtcars)
+fit4 <- lm(mpg ~ 0 + cyl, mtcars)
 
 # zero weights used to break influence columns in augment.lm
 wts <- c(0, rep(1, nrow(mtcars) - 1))
@@ -60,8 +61,9 @@ test_that("glance.lm", {
   gl <- glance(fit)
   gl2 <- glance(fit2)
   gl3 <- glance(fit3)
+  gl4 <- glance(fit4)
 
-  check_glance_outputs(gl, gl2, gl3)
+  check_glance_outputs(gl, gl2, gl3, gl4)
 })
 
 test_that("augment.lm", {
@@ -141,3 +143,11 @@ test_that("augment.lm", {
     "\\`level\\` argument is not supported in the \\`augment\\(\\)\\` method for \\`lm\\` objects"
   )
 })
+
+test_that("glance.lm returns non-NA entries with 0-intercept model (#1209)", {
+  fit <- lm(mpg ~ 0 + cyl, mtcars)
+  fit_glance <- glance(fit)
+  expect_false(is.na(fit_glance[["statistic"]]))
+  expect_false(is.na(fit_glance[["p.value"]]))
+  expect_false(is.na(fit_glance[["df"]]))
+})