NEWS

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r4clinstats 0.3.3

• learn() with no argument now lists the lessons and returns to the > prompt, without the numbered pick-list. That list numbered from 1 while the modules start at m0, so a learner who typed 10 for "m10 Describing data" was taken to m9, Summary tables. Its Selection: prompt also rejected R code, and a tester typed learn("m10") into it twice before trying a number. learn("m10") is now the one way to open a lesson, everywhere.
• Comparing groups explains the ten columns tidy() returns for a t-test, and how to read the sign of estimate: it is the first group minus the second, in alphabetical order, so renaming the arms can flip it.
• Regression explains se = FALSE, and what the grey band it hides actually shows: a confidence interval for the line, not the spread of patients.
• The crib sheet is written so it works on any data. Each entry is a template with the parts you replace highlighted, and an example from the lessons beneath it, so it is clear which words are yours and which are R's. That matters most for quote marks, which summary_factorlist() needs round column names and filter() does not.

r4clinstats 0.3.2

• The install no longer names the rstudio R-universe alongside CRAN. That universe also serves development builds of learnr and rmarkdown, and install.packages() takes the highest version it can see rather than the first repository listed, so the one-command install in 0.3.1 quietly put learners on an unreleased learnr: the engine every lesson runs on. The course now installs from CRAN and its own R-universe, and check_setup() fetches gradethis on its own afterwards. .install_missing() keeps the two apart for the same reason.
• install-check tests the two-step guide as written and fails if a development build of learnr or rmarkdown reaches a learner's library. This was found by running that job against a genuinely clean machine, which is the only place it was visible.

r4clinstats 0.3.1

• gradethis moved from Posit's posit-dev R-universe to rstudio. The old server still answers, so installs failed with R's misleading "package 'gradethis' is not available for this version of R" rather than anything pointing at the real cause. Every reference now names the new server: check_setup(), the automatic installer, DESCRIPTION and the guides.
• check_setup() now asks whether gradethis is actually in the repository rather than whether the server answers. Through the whole outage above the old check reported [OK ], because the server it tested stayed up after the package left it. A moved package is now named as such, with somewhere to report it.
• The course installs from https://apsmunro.r-universe.dev instead of remotes::install_github(). GitHub allows 60 anonymous API requests an hour per network address, which a hospital or university shares across everyone behind it, so a group installing together hit HTTP 403. R-universe has no such limit and serves a Windows binary. Troubleshooting gained an entry for the 403, with a tarball fallback for networks that block R-universe.
• Dropped the Remotes: field, which made every install resolve a second GitHub repository. CI now names the R-universe in extra-repositories instead: that field, not Additional_repositories, is what the dependency solver reads, and removing Remotes: without it broke both workflows.
• A weekly install-check job installs the course from R-universe on Windows exactly as a learner would, then runs check_setup(). The next time this path breaks, CI notices rather than a clinician.

r4clinstats 0.3.0

• M14, Reproducible reports: the capstone, and the course is complete. The learner rebuilds the whole trial analysis as six graded exercises (no blanks, for the first time in the course), then leaves the sandbox: start_report() copies a Quarto report template with matching TODO chunks into their working directory, and the lesson ends with a real rendered document. The scaffold renders as shipped, so the render-early habit works from minute zero; start_report(completed = TRUE) is the escape hatch.
• The closing bookend: M14 returns to the four core books introduced in M0, and adds a five-step guide to starting a real project with your own data.
• Both report templates are tested chunk by chunk (and inline expression by inline expression) in CI.

r4clinstats 0.2.1

• learn() groups the menu by course part, matching the website.
• Every graded exercise with a targeted catch now declares its common wrong answer in the tutorial source, and the test harness verifies the catch fires with the intended feedback. This found and fixed a real hole: M4's quoted-threshold mistake (bmi >= "30") used to pass by coincidence; the grader now catches it and explains why text comparison is a trap.
• CI also runs on Windows, where the course's learners actually are.

r4clinstats 0.2.0

• Part 3, the analysis modules: M10 Describing data, M11 Comparing groups, M12 Regression, and M13 Survival analysis.
• The outcomes dataset: one year of follow-up for the patients cohort, with response, adverse events, and a censored time-to-event pair. Effect sizes were tuned so the planted signals survive the seed (response OR 2.66, hazard ratio 0.47, both clear of 1).
• The analysis arc is deliberate: baseline balance (no test needed), then the change-score t-test (p = 0.039), then the baseline-adjusted model that sharpens it (p = 0.002) — regression to the mean and ANCOVA taught with the course's own trial.
• check_setup() now also checks survival and broom.

r4clinstats 0.1.0

• Four new modules: M6 Reading & cleaning data, M7 Visualisation I, M8 Visualisation II, and M9 Summary tables, with the synthetic linelist dataset for the cleaning lesson.
• M9 now teaches when a baseline table should carry p-values and when it should not: a randomised trial's Table 1 describes the arms without testing them (CONSORT), so the p = TRUE exercises compare non-randomised groups.
• Plot exercises accept aesthetics mapped inside the geom as well as in ggplot(), and the faceting exercises check the faceting variable rather than only that faceting happened (facet_grid() is accepted too).
• M3 trimmed so it no longer repeats M1's tidy-data material, and retitled Wrangling I to match the menu.
• The test harness now feeds every canonical solution through its own gradethis grader and asserts a pass, and checks that every graded exercise has a hint and a solution.
• Monthly scheduled CI run, so a breaking tidyverse release surfaces on a schedule rather than in a learner's session.

r4clinstats 0.0.0.9000

• The MVP: modules M0-M5, the patients and labs datasets, learn(), check_setup(), use_local_library(), the pkgdown portal with the webR taster, and the solution-running test harness.