Try to fix coverage together

.github/workflows/test-coverage.yaml

@@ -8,43 +8,54 @@ on:
 
 name: test-coverage
 
+permissions: read-all
+
 jobs:
   test-coverage:
     runs-on: ubuntu-latest
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-r@v2
         with:
           use-public-rspm: true
 
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          extra-packages: any::covr
+          extra-packages: any::covr, any::xml2
           needs: coverage
 
       - name: Test coverage
         run: |
-          covr::codecov(
+          cov <- covr::package_coverage(
             quiet = FALSE,
             clean = FALSE,
-            install_path = file.path(Sys.getenv("RUNNER_TEMP"), "package")
+            install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
           )
+          covr::to_cobertura(cov)
         shell: Rscript {0}
 
+      - uses: codecov/codecov-action@v4
+        with:
+          fail_ci_if_error: ${{ github.event_name != 'pull_request' && true || false }}
+          file: ./cobertura.xml
+          plugin: noop
+          disable_search: true
+          token: ${{ secrets.CODECOV_TOKEN }}
+
       - name: Show testthat output
         if: always()
         run: |
           ## --------------------------------------------------------------------
-          find ${{ runner.temp }}/package -name 'testthat.Rout*' -exec cat '{}' \; || true
+          find '${{ runner.temp }}/package' -name 'testthat.Rout*' -exec cat '{}' \; || true
         shell: bash
 
       - name: Upload test results
         if: failure()
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: coverage-test-failures
           path: ${{ runner.temp }}/package

README.Rmd

@@ -23,20 +23,20 @@ knitr::opts_chunk$set(
 [![License](https://img.shields.io/badge/License-GPL_v2-blue.svg)](https://github.com/jan-imbi/adestr/blob/master/LICENSE.md)
 <!-- badges: end -->
 
-
 This package implements methods to evaluate the performance characteristics
 of various point and interval estimators for adaptive two-stage designs with 
 prespecified sample-size recalculation rules. Further, it allows for
 evaluation of these estimators on real datasets, and it implements methods
 to calculate p-values.
 
 Currently, it works for designs objects which were produced by the
-R-package `adoptr`, which calculates optimal design parameters adaptive
+R-package [`adoptr`](https://github.com/optad/adoptr), which calculates optimal design parameters adaptive
 two-stage designs.
 
 An introductory vignette covering common usecases is given at [https://jan-imbi.github.io/adestr/articles/Introduction.html](https://jan-imbi.github.io/adestr/articles/Introduction.html).
 
-The test [https://jan-imbi.github.io/adestr/articles/Introduction.html](https://jan-imbi.github.io/adestr/articles/Introduction.html).
+This package comes suite of unit tests. The code of the test cases can be viewed here: [https://github.com/jan-imbi/adestr/tree/master/tests/testthat](https://github.com/jan-imbi/adestr/tree/master/tests/testthat). The authors assume no responsibility for the correctness of the
+code or results produced by its usage. Use at your own risk.
 
 <!-- reference implementation verlinken -->
 

README.md

@@ -19,8 +19,19 @@ Further, it allows for evaluation of these estimators on real datasets,
 and it implements methods to calculate p-values.
 
 Currently, it works for designs objects which were produced by the
-R-package `adoptr`, which calculates optimal design parameters adaptive
-two-stage designs.
+R-package [`adoptr`](https://github.com/optad/adoptr), which calculates
+optimal design parameters adaptive two-stage designs.
+
+An introductory vignette covering common usecases is given at
+<https://jan-imbi.github.io/adestr/articles/Introduction.html>.
+
+This package comes suite of unit tests. The code of the test cases can
+be viewed here:
+<https://github.com/jan-imbi/adestr/tree/master/tests/testthat>. The
+authors assume no responsibility for the correctness of the code or
+results produced by its usage. Use at your own risk.
+
+<!-- reference implementation verlinken -->
 
 ## Installation
 
@@ -32,22 +43,14 @@ remotes::install_github("https://github.com/jan-imbi/adestr")
 
 into your R console.
 
-## Information for reviewers
-
-The scripts to reproduce the results from the paper can be found in the
-`/data/code/` directory of this repository. The results themselves are
-located in the `/data/` directory.
-
-The easiest way to inspect the results is to [clone this
-repository](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository).
-
-## General example for usage of the package
+## Small introductory example
 
 Here is a quick example showing the capabilities of `adestr`. First,
 load `adestr`:
 
 ``` r
 library(adestr)
+#> Loading required package: adoptr
 ```
 
 Then, you can evaluate the performance of an estimator like this:
@@ -129,3 +132,7 @@ analyze(
 #>  SWCF ordering p-value:                                               0.01097483
 #>  LR test ordering p-value:                                          6.653031e-05
 ```
+
+Please refer to
+<https://jan-imbi.github.io/adestr/articles/Introduction.html> for a
+more detailed introduction.

tests/testthat/test_helpers.R

@@ -0,0 +1,17 @@
+test_that("Transformation convenience functions work",
+{
+  expect_equal(t_to_z(z_to_t(1.234, 1.3, 2.1, 23), 1.3, 2.1, 23), 1.234)
+  expect_equal(smean_to_t(1.2, 3.4, 45, FALSE), 1.2/sqrt(3.4) * sqrt(45))
+  expect_equal(smeans_to_smean(1, 2, 30, 30), 1.5)
+  expect_equal(svar_to_se(2.3, 40, FALSE), sqrt(2.3/40))
+  expect_equal(t_test(1.2, 3.4, 50, FALSE), 1.2/sqrt(3.4)*sqrt(50))
+  expect_equal(pool_svar1_svar2(1.2, 3.4, 50, 60, FALSE), (49 * 1.2 + 59 * 3.4) / (108))
+})
+
+
+
+test_that("Generation of example statistics doesn't produce an error",
+{
+  expect_error(get_example_statistics(), NA)
+  expect_error(get_statistics_from_paper (), NA)
+})

vignettes/Introduction.Rmd

@@ -27,17 +27,22 @@ to calculate p-values.
 Currently, it works for designs objects which were produced by the
 R-package `adoptr`, which calculates optimal design parameters for
 adaptive two-stage designs. You can learn about adoptr here:
-[kkmann.github.io/adoptr/](https://kkmann.github.io/adoptr/).
+[optad.github.io/adoptr/](https://optad.github.io/adoptr/).
+
+An introductory vignette covering common usecases is given at [https://jan-imbi.github.io/adestr/articles/Introduction.html](https://jan-imbi.github.io/adestr/articles/Introduction.html).
+
+This package comes suite of unit tests. The code of the test cases can be viewed here: [https://github.com/jan-imbi/adestr/tree/master/tests/testthat](https://github.com/jan-imbi/adestr/tree/master/tests/testthat). The authors assume no responsibility for the correctness of the
+code or results produced by its usage. Use at your own risk.
 
 # Fitting a design with adoptr
 In order to showcase the capabilities of this package, we need a trial design first.
-We refer to [the example from the adoptr documentation](https://kkmann.github.io/adoptr/articles/adoptr.html)
+We refer to [the example from the adoptr documentation](https://optad.github.io/adoptr/articles/adoptr.html)
 for this.
 You can read more about optimal adaptive designs fitted via the adoptr package here:
-[kkmann.github.io/adoptr/articles/adoptr_jss.html](https://kkmann.github.io/adoptr/articles/adoptr_jss.html).
+[optad.github.io/adoptr/articles/adoptr_jss.html](https://optad.github.io/adoptr/articles/adoptr_jss.htmll).
 
 For the sake of this introduction, a pre-computed version of the first example from
-[kkmann.github.io/adoptr/articles/adoptr.html](https://kkmann.github.io/adoptr/articles/adoptr.html)
+[optad.github.io/adoptr/articles/adoptr.html](https://optad.github.io/adoptr/articles/adoptr.html)
 is provided with this package via the `get_example_design` function.
 
 ```{r}