CRAN release v0.1.1 [skip vbump] (#45)

Closes #44 #39 --------- Co-authored-by: shajoezhu <sha.joe.zhu@gmail.com>
insightsengineering · Dec 8, 2023 · 91cb92a · 91cb92a
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -2,7 +2,7 @@ Type: Package
 Package: tern.gee
 Title: Tables and Graphs for Generalized Estimating Equations (GEE) Model
     Fits
-Version: 0.1.0.9009
+Version: 0.1.1
 Date: 2023-11-28
 Authors@R: c(
     person("Daniel", "Sabanés Bové", , "daniel.sabanes_bove@roche.com", role = c("aut", "cre")),
@@ -16,15 +16,15 @@ URL: https://github.com/insightsengineering/tern.gee/
 BugReports: https://github.com/insightsengineering/tern.gee/issues
 Depends:
     R (>= 4.0),
-    tern (>= 0.7.10)
+    tern (>= 0.9.3)
 Imports:
     checkmate,
     emmeans (>= 1.4.5),
-    formatters,
+    formatters (>= 0.5.5),
     geeasy,
     geepack,
     nlme,
-    rtables,
+    rtables (>= 0.6.6),
     stats
 Suggests:
     dplyr,
@@ -34,8 +34,6 @@ Suggests:
     vdiffr
 VignetteBuilder:
     knitr
-Remotes:
-    insightsengineering/tern@*release
 Config/testthat/edition: 3
 Encoding: UTF-8
 Language: en-US

diff --git a/NEWS.md b/NEWS.md
@@ -1,13 +1,9 @@
-# tern.gee 0.1.0.9009
+# tern.gee 0.1.1
 
-### Miscellaneous
-
-* Add badges to README.
+* Added badges to README.
 
 # tern.gee 0.1.0
 
-### Enhancements
-
-* First release
-* Update pkgdown site, introduction vignette, and README, add unit tests.
-* Add examples for `fit_gee`, `lsmeans`, `s_lsmeans_logistic`, `summarize_gee_logistic`.
+* First release.
+* Updated pkgdown site, introduction vignette, and README, added unit tests.
+* Added examples for `fit_gee`, `lsmeans`, `s_lsmeans_logistic`, `summarize_gee_logistic`.
diff --git a/R/data.R b/R/data.R
diff --git a/README.md b/README.md
@@ -43,19 +43,20 @@ However if you use another reporting framework then it will be better to directl
 
 ## Installation
 
-### GitHub
+`tern.gee` is available on CRAN and you can install the latest released version with:
 
-It is recommended that you [create and use a Github PAT](https://docs.github.com/en/github/authenticating-to-github/keeping-your-account-and-data-secure/creating-a-personal-access-token) to install the latest version of this package. Once you have the PAT, run the following:
+``` r
+install.packages("tern.gee")
+```
 
-```r
-Sys.setenv(GITHUB_PAT = "your_access_token_here")
+or you can install the latest development version directly from GitHub by running the following:
+
+``` r
 if (!require("remotes")) install.packages("remotes")
-remotes::install_github("insightsengineering/tern.gee@*release")
+remotes::install_github("insightsengineering/tern.gee")
 ```
 
-### `NEST` distribution
-
-A stable release of all `NEST` packages is also available [here](https://github.com/insightsengineering/depository#readme).
+Note that it is recommended you [create and use a `GITHUB_PAT`](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token) if installing from GitHub.
 
 ## Getting started
 

diff --git a/man/fev_data.Rd b/man/fev_data.Rd
diff --git a/tests/testthat/_snaps/tabulate_gee.md b/tests/testthat/_snaps/tabulate_gee.md
@@ -0,0 +1,44 @@
+# h_gee_cov works as expected
+
+    Code
+      result
+    Output
+              VIS1      VIS2      VIS3      VIS4  
+      ————————————————————————————————————————————
+      VIS1   1.0000    -0.0565   -0.1257   0.0678 
+      VIS2   -0.0565   1.0000    -0.0836   -0.0578
+      VIS3   -0.1257   -0.0836   1.0000    0.0092 
+      VIS4   0.0678    -0.0578   0.0092    1.0000 
+
+# summarize_gee_logistic works as expected with covariates in the model
+
+    Code
+      result
+    Output
+                                          PBO            TRT     
+                                        (N=105)         (N=95)   
+      ———————————————————————————————————————————————————————————
+      n                                   420            380     
+      Adjusted Mean Proportion (SE)   0.90 (0.02)    0.95 (0.01) 
+        95% CI                        (0.85, 0.93)   (0.91, 0.97)
+      Odds Ratio                                         1.97    
+        95% CI                                       (1.03, 3.77)
+      Log Odds Ratio                                     0.68    
+        95% CI                                       (0.03, 1.33)
+
+# summarize_gee_logistic works as expected with no covariates in the model
+
+    Code
+      result
+    Output
+                                          PBO            TRT     
+                                        (N=105)         (N=95)   
+      ———————————————————————————————————————————————————————————
+      n                                   420            380     
+      Adjusted Mean Proportion (SE)   0.88 (0.02)    0.94 (0.01) 
+        95% CI                        (0.84, 0.92)   (0.91, 0.97)
+      Odds Ratio                                         2.18    
+        95% CI                                       (1.16, 4.10)
+      Log Odds Ratio                                     0.78    
+        95% CI                                       (0.15, 1.41)
+
diff --git a/tests/testthat/test-tabulate_gee.R b/tests/testthat/test-tabulate_gee.R
@@ -10,37 +10,26 @@ model <- fit_gee(
 )
 
 # to do: finish test once h_gee_coef is working correctly
-test_that("h_gee_coef works as expected", {
-  # result <- expect_silent(h_gee_coef(model))
-  # result2 <- as.rtable(model, type = "coef", format = "xx.xxxx")
-  # expect_identical(result, result2)
-  #
-  # result_matrix <- to_string_matrix(result)
-  # expected_matrix <- structure(
-  #   c(
-  #   ),
-  #   dim = c()
-  # )
-  # expect_identical(result_matrix, expected_matrix)
-})
+# test_that("h_gee_coef works as expected", {
+# result <- expect_silent(h_gee_coef(model))
+# result2 <- as.rtable(model, type = "coef", format = "xx.xxxx")
+# expect_identical(result, result2)
+#
+# result_matrix <- to_string_matrix(result)
+# expected_matrix <- structure(
+#   c(
+#   ),
+#   dim = c()
+# )
+# expect_identical(result_matrix, expected_matrix)
+# })
 
 test_that("h_gee_cov works as expected", {
   result <- expect_silent(h_gee_cov(model))
   result2 <- as.rtable(model, type = "cov", format = "xx.xxxx")
   expect_identical(result, result2)
 
-  result_matrix <- to_string_matrix(result)
-  expected_matrix <- structure(
-    c(
-      "", "VIS1", "VIS2", "VIS3", "VIS4",
-      "VIS1", "1.0000", "-0.0565", "-0.1257", "0.0678",
-      "VIS2", "-0.0565", "1.0000", "-0.0836", "-0.0578",
-      "VIS3", "-0.1257", "-0.0836", "1.0000", "0.0092",
-      "VIS4", "0.0678", "-0.0578", "0.0092", "1.0000"
-    ),
-    dim = c(5L, 5L)
-  )
-  expect_identical(result_matrix, expected_matrix)
+  expect_snapshot(result)
 })
 
 test_that("s_lsmeans_logistic works as expected when not in reference column", {
@@ -81,16 +70,7 @@ test_that("summarize_gee_logistic works as expected with covariates in the model
       alt_counts_df = dat_adsl
     )
 
-  result_matrix <- to_string_matrix(result)
-  expected_matrix <- structure(
-    c(
-      "", "", "n", "Adjusted Mean Proportion (SE)", "95% CI", "Odds Ratio", "95% CI", "Log Odds Ratio", "95% CI",
-      "PBO", "(N=105)", "420", "0.90 (0.02)", "(0.85, 0.93)", "", "", "", "",
-      "TRT", "(N=95)", "380", "0.95 (0.01)", "(0.91, 0.97)", "1.97", "(1.03, 3.77)", "0.68", "(0.03, 1.33)"
-    ),
-    dim = c(9L, 3L)
-  )
-  expect_identical(result_matrix, expected_matrix)
+  expect_snapshot(result)
 })
 
 test_that("summarize_gee_logistic works as expected with no covariates in the model", {
@@ -115,14 +95,5 @@ test_that("summarize_gee_logistic works as expected with no covariates in the mo
       alt_counts_df = dat_adsl
     )
 
-  result_matrix <- to_string_matrix(result)
-  expected_matrix <- structure(
-    c(
-      "", "", "n", "Adjusted Mean Proportion (SE)", "95% CI", "Odds Ratio", "95% CI", "Log Odds Ratio", "95% CI",
-      "PBO", "(N=105)", "420", "0.88 (0.02)", "(0.84, 0.92)", "", "", "", "",
-      "TRT", "(N=95)", "380", "0.94 (0.01)", "(0.91, 0.97)", "2.18", "(1.16, 4.10)", "0.78", "(0.15, 1.41)"
-    ),
-    dim = c(9L, 3L)
-  )
-  expect_identical(result_matrix, expected_matrix)
+  expect_snapshot(result)
 })