add tests for residual.R, bump up version (#433)

DESCRIPTION

@@ -1,14 +1,14 @@
 Type: Package
 Package: mmrm
 Title: Mixed Models for Repeated Measures
-Version: 0.3.10.9006
+Version: 0.3.11
 Authors@R: c(
     person("Daniel", "Sabanes Bove", , "[email protected]", role = c("aut", "cre")),
+    person("Liming", "Li", , "[email protected]", role = "aut"),
     person("Julia", "Dedic", , "[email protected]", role = "aut"),
     person("Doug", "Kelkhoff", , "[email protected]", role = "aut"),
     person("Kevin", "Kunzmann", , "[email protected]", role = "aut"),
     person("Brian Matthew", "Lang", , "[email protected]", role = "aut"),
-    person("Liming", "Li", , "[email protected]", role = "aut"),
     person("Christian", "Stock", , "[email protected]", role = "aut"),
     person("Ya", "Wang", , "[email protected]", role = "aut"),
     person("Craig", "Gower-Page", , "[email protected]", role = "ctb"),

NEWS.md

@@ -1,13 +1,15 @@
-# mmrm 0.3.10.9006
-
-### Miscellaneous
-
-- Fix internal test skipping functions for MacOS R. 
+# mmrm 0.3.11
 
 ### Bug Fixes
 
 - Previously if a secondary optimizer fails `mmrm` will fail. This is fixed now.
-- Previously character covariate variable will make `Anova` fail. This is fixed now.
+- Previously character covariate variables will make `Anova` fail. This is fixed now.
+
+# mmrm 0.3.10
+
+### Miscellaneous
+
+- Fix internal test skipping functions for MacOS R. 
 
 # mmrm 0.3.9
 

tests/testthat/test-residual.R

@@ -0,0 +1,29 @@
+# h_df_1d_res ----
+
+test_that("h_df_1d_res works as expected", {
+  fit <- get_mmrm()
+  contrast <- numeric(length = length(coef(fit)))
+  contrast[2] <- 1
+  result <- expect_silent(h_df_1d_res(fit, contrast))
+  expect_list(result)
+  expect_equal(result$est, 1.5305, tolerance = 1e-3)
+  expect_equal(result$se, 0.6245, tolerance = 1e-3)
+  expect_identical(result$df, 526L)
+  expect_equal(result$t_stat, 2.4509, tolerance = 1e-3)
+  expect_equal(result$p_val, 0.01458, tolerance = 1e-3)
+})
+
+# h_df_md_res ----
+
+test_that("h_df_md_res works as expected", {
+  fit <- get_mmrm()
+  contrast <- matrix(data = 0, ncol = length(coef(fit)), nrow = 2)
+  contrast[1, 2] <- 1
+  contrast[2, 3] <- 1
+  result <- expect_silent(h_df_md_res(fit, contrast))
+  expect_list(result)
+  expect_identical(result$num_df, 2L)
+  expect_identical(result$denom_df, 526L)
+  expect_equal(result$f_stat, 36.9114, tolerance = 1e-3)
+  expect_true(result$p_val < 1e-10)
+})