ClinicoPath Org Collection

A 205-repository reference library of jamovi modules, the framework’s own plumbing, and the R packages the analyses are built on — a reading collection, not where the live modules are developed.

Purpose

The ClinicoPath GitHub organisation is a collection: forks and mirrors of jamovi itself, of around fifty third-party jamovi modules, of the R packages that the ClinicoPath analyses wrap, plus teaching material and datasets. 205 repositories, read 2026-07-28.

It answers a different question from the six module pages already in this wiki. Those describe what we ship. This describes what is available to read when building something new — how other people solved a problem, which R package already does the thing, what the framework expects.

Read this first: the org copies are stale

The organisation contains repositories named ClinicoPathJamoviModule, ClinicoPathDescriptives, jsurvival, meddecide, jjstatsplot, OncoPath and ClinicoPath. These are not the live modules. Their last updates run from May 2020 to November 2024. The live modules are under the personal account and are what every other page in this wiki describes:

Live (use this) Org copy (do not)
github.com/sbalci/ClinicoPathJamoviModule — v1.0.1, 388 analyses ClinicoPath/ClinicoPathJamoviModule — Nov 2024
github.com/sbalci/ClinicoPathDescriptives ClinicoPath/ClinicoPathDescriptives — Jul 2020
github.com/sbalci/jsurvival ClinicoPath/jsurvival — Jul 2020
github.com/sbalci/meddecide ClinicoPath/meddecide — Jul 2020
github.com/sbalci/jjstatsplot ClinicoPath/jjstatsplot — Jul 2020
github.com/sbalci/OncoPath ClinicoPath/OncoPath — Sep 2025

Cloning the org copy of a module you already maintain is the one concrete way this collection can waste an afternoon, which is why it is the first thing on the page. See ClinicoPath jamovi Module for what the live umbrella actually contains.

Data used

Four dataset repositories, worth knowing about because they solve the “I need an example cohort that is not patient data” problem:

  • medicaldata and medicaldata-1 — the R medicaldata package: real, de-identified clinical datasets curated for teaching. The natural source for a worked example in a vignette.
  • Rdatasets — the aggregated collection of datasets shipped inside R packages.
  • lsj-data — data files for Learning Statistics with jamovi, chapter by chapter.

Methods

What is in the collection, grouped by what you would reach for it for. Counts are approximate where a group has near-duplicate mirrors.

The framework itself, and its plumbing

jamovi (the TypeScript application), jmv and jmv-1 (the analyses as an R package), jmvcore and jmvcore-1 (the framework classes every module inherits), jmvtools and jmvtools-1 (the build and install tooling), jamovi-compiler, jmvconnect (drive jamovi from R), jmvReadWrite (read and write .omv files from R), jamovi-readstat (SPSS, SAS and Stata import), jamovi-library, jamovi-deval, r-portable-windows.

Two of these are worth more than reference value. jmvReadWrite is the escape hatch: it makes a .omv file readable from a script, so a jamovi analysis can be checked, diffed or regression- tested outside the GUI — which is otherwise hard. jamovi-readstat is the reason an SPSS file from a collaborator opens without conversion.

Templates and worked examples for building a module

jamoviTemplate (a minimal skeleton), jmvexamples (analyses built up step by step), jmvbaseR (base-R analyses exposed as a module — a readable mid-sized example), jamovi-modules, jamoviDocs. These are the ones to open when the question is “how is this supposed to be structured”, and they are what jamovi Module Development is written from.

Third-party jamovi modules (~55)

The largest and most useful group: other people’s answers to problems that recur here.

  • Regression and general models — gamlj (GLM, mixed and generalized models; the most-forked module in the collection at 14), gamlj_glm, jamovi-lmR, jamovi_mixed, walrus (robust methods), BrawStats-for-Jamovi and variants.
  • SEM, mediation and paths — semlj, pathj, jamm (advanced mediation), medmod, longsem (longitudinal SEM), Composite-SEM.
  • Psychometrics — snowIRT, snowRMM, snowLatent (latent class), Rasch, jamoviPsychoPDA, cNORM_JAMOVI (continuous norming), esci (effect sizes and intervals).
  • Clustering and multivariate — snowCluster, hca, clusterParty, MTUcluster, MVN_jamovi (multivariate normality: 6 MV and 5 UV tests with diagnostics), seolmatrix, PartialProximity, Correlations.
  • Diagnostic and medical — DiagROC (ROC with diagnostic accuracy tools), Kappa, ppv (demonstrates positive predictive value), ChiSquaredTools (post-hoc tests, association measures, stratified analysis), MAJOR and JamoviMeta (meta-analysis).
  • Plots and tables — vijPlots (histogram, box, point, bar, line, plus Likert and multiple-response), jmvplots, scatr, surveymv, Jamovi-TrialPlots (clinical trial visualisations), SummaryTables.
  • Data handling — jTransform (dataset transformations), jReshape (long/wide), SuperCode (nominal variable encoding), SimpleTests, SimpleSurvival.
  • Power — jpower, pamlj.
  • Machine learning — TreeModels, jamovi-plugin-for-machine-learning, casnet-jmv.
  • Teaching and other — clt (central limit theorem), Statkat (test selection), jmvarcade, bf_jamovi (BayesFactor), PUBH5018-jamovi.
  • askLLM — the most recently touched repository in the collection, and the one item from it evaluated in full. An LLM question-answering interface inside jamovi. Not adopted, but worth installing for its documentation: its author measured his own module’s hallucination rate, published the wrong menu paths verbatim, grounded the model in a scanned catalogue of real menus, and measured again — 18 of 18 references then matched exactly. That technique transfers directly to LLM Report-Quality Checking, which is the reason the page exists.

The R packages the analyses are built on

Mirrored so the implementation can be read without leaving the collection.

  • Tables and summaries — gtsummary, tableone, arsenal, summarytools, crosstable, sumvar, tangram, janitor, finalfit, report, DataExplorer, explore, autoEDA. These are the reference implementations behind Descriptive Tables.
  • Plotting — ggstatsplot (what jjstatsplot wraps), tidyplots, ggswim (swimmer plots), ggoncoplot, ggEDA, ggrain, ggconsort (CONSORT diagrams), ggupset, complex-upset, UpSetR, ggvenn, waffle, easyalluvial, vtree, DiagrammeR, nomogrammer, flexplot, bbplot, R-graph-gallery.
  • Survival — survival, survminer, survcomp, survivalROC (time-dependent ROC), censored, jskm, KMunicate-package (KMunicate-style KM plots), bayesdca, iwillsurvive, deathwatch. The substrate for Survival Analysis Workflow.
  • Agreement, epidemiology and decisions — irr, kappaSize (sample size for interobserver agreement studies), SimplyAgree, epiR, RVAideMemoire, chisq.posthoc.test, FFTrees (fast-and-frugal decision trees). Relevant to Interobserver Agreement and Decision Curve Analysis.
  • Machine learning and statistical infrastructure — caret, mlr3extralearners, extraTrees, rpart, ppsr, seriation, correlation, corrr, mixOmics, syndRomics, optimall, benford.analysis.
  • Utility — dplyr, magrittr, knitr, rmarkdown, units, eurostat, textreadr, clintools, clinDataReview.

Teaching material and documentation

lsj-book and lsj-data (Learning Statistics with jamovi), Sourcebook, stat_jamovi, jamoviguide.com, jamoviref, statistics_jamovi, StatLab_jamovi, dev.jamovi.org, plus per-module documentation sites (gamlj.github.io, jamm_docs, jamoviPsychoPDA_docs, ClinicoPath.github.io).

Deployment

shinyproxy and shinyproxy-template — the route to serving an R analysis as a hosted app rather than as a jamovi module, which is a different distribution decision entirely. histopathJulia is an outlier: histopathology analysis in Julia, from January 2021, apparently not pursued.

Current state / open questions

  • Is the collection still being curated, or is it an archive? Most repositories were last touched between 2017 and 2021, but askLLM (Jul 2026), SuperCode (May 2026), SummaryTables (May 2026), MVN_jamovi (Mar 2026) and Jamovi-TrialPlots (Feb 2026) are recent. So it is active, but sparsely. Nothing records what the intake rule is. [unverified]
  • Should the stale ClinicoPath mirrors be archived on GitHub? Marking them archived would make the “which one do I clone” question answer itself, and costs nothing.
  • Which of the third-party modules are actually installed and used, as opposed to collected? That distinction is not visible from the repository list and would change what is worth reading first. askLLM has since been evaluated (askLLM); DiagROC, ChiSquaredTools and MVN_jamovi remain the strongest candidates on subject matter alone.
  • Does anything in the collection duplicate an analysis already in the umbrella’s 388? Worth a pass once, because the umbrella is large enough that rediscovering a capability is plausible.

How it connects

jamovi Module Development — the concept this collection is the raw material for; the framework plumbing and templates above are what that page is written from.

ClinicoPath jamovi Module — the live umbrella module, 388 analyses, and the reason the stale org mirrors matter enough to warn about at the top of this page.

jjstatsplot — the clearest case of the collection’s purpose: it wraps ggstatsplot, and ggstatsplot is mirrored here.

Descriptive Tables — gtsummary, tableone, arsenal and finalfit are the reference implementations of exactly what that page describes.

Survival Analysis Workflow — survival, survminer, jskm and KMunicate-package are the packages underneath it, and survivalROC and bayesdca extend it.

LLM Report-Quality Checking — askLLM puts an LLM inside jamovi, which is the same question that page asks approached from the tooling side rather than the prompt side.

Derived from: the organisation’s repository listing at github.com/orgs/ClinicoPath/repositories, all seven pages, read 2026-07-28; the repo: fields of the six existing module pages in this wiki compared against the org’s copies to establish which are stale. Individual repositories in the collection were not cloned — this is a catalogue, and anything adopted from it needs its own read.