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Function Reference Guide

ClinicoPath Team

2026-08-14

Source: vignettes/function-reference.Rmd
function-reference.Rmd

ClinicoPathJamoviModule Function Reference

Analyses documented here: 18, selected as a starting point for each menu group Analyses in the module: 420+, of which about 60 are currently on a production menu; the rest are on development or test menu routes and do not appear in jamovi yet Menu Groups: 5 (ClinicoPathDescriptives, JJStatsPlot, OncoPath, jsurvival, meddecide) Status Categories: Stable, To be Tested, Drafts

GitHub: ClinicoPathJamoviModule Documentation: www.serdarbalci.com/ClinicoPathJamoviModule

How to Use This Reference

This guide introduces a representative analysis from each menu group - 18 in all - organized by:

  • Menu Group: Where to find the function in jamovi’s menu
  • Status: Stability and testing status
  • Purpose: What the function does
  • When to Use: Clinical and research scenarios
  • Test Data: Available example datasets

Function Status Levels

  • Stable: Production-ready, thoroughly tested
  • To be Tested: Functional but needs more validation
  • Drafts: Work in progress, may have limitations

These levels describe testing maturity, which is a separate question from whether an analysis appears in a jamovi menu. Most of the module’s 420+ analyses are on development or test menu routes and are not yet reachable from the menus, whatever their testing status. Every analysis documented in this guide is both Stable and on a production menu.

Quick Navigation

ClinicoPathDescriptives

Comprehensive descriptive statistics and data quality tools for clinical research.

Stable Functions

agepyramid

Internal: agepyramid Purpose: Population pyramid visualization When to use: Demographic analysis, cohort characterization, age-gender distribution Test Data: 1 .omv file

tableone

Internal: tableone Purpose: Generate publication-ready “Table 1” with baseline characteristics When to use: Manuscript preparation, clinical trial baseline tables, cohort comparison Test Data: 1 .omv file

crosstable

Internal: crosstable Purpose: Advanced contingency tables with percentages and statistics When to use: Categorical variable comparisons, disease vs. exposure, treatment outcomes Test Data: 1 .omv file

summarydata

Internal: summarydata Purpose: Comprehensive summary statistics for continuous and categorical variables When to use: Exploratory data analysis, descriptive statistics, data overview Test Data: 1 .omv file

meddecide

Medical decision analysis, diagnostic test evaluation, and agreement studies.

✨ NEW: Kappa Sample Size Functions (January 2025)

Three complementary functions for comprehensive kappa agreement study planning:

kappasizeci ✨

Internal: kappaSizeCI Purpose: Sample size for kappa estimation (precision approach) When to use: Planning agreement studies, method validation, estimating true agreement Approach: “How many subjects to estimate kappa within ±X?” Test Data: - Comprehensive scenarios (86 scenarios) - Relationship cases - Validation cases

Key Features: - Confidence interval-based precision - 2-5 outcome categories - 2-5 raters - Binary, ordinal, continuous outcomes

kappasizefixedn ✨

Internal: kappaSizeFixedN Purpose: Reverse calculation - detectable kappa for fixed sample size When to use: Resource-constrained studies, completed trials, QA programs, feasibility Approach: “What can I detect with my fixed n?” Test Data: - Comprehensive scenarios (86 scenarios) - Power cases - Validation cases

Constraint Types: - Budget constraints - Time constraints - Case availability (rare diseases) - Regulatory requirements - Completed studies (retrospective) - QA protocols (fixed annual samples)

kappasizepower ✨

Internal: kappaSizePower Purpose: Sample size for kappa hypothesis testing (power approach) When to use: Planning studies to test agreement hypotheses, comparing to threshold Approach: “How many to test κ₁ vs. κ₀ with power X?” Test Data: - Comprehensive scenarios (86 scenarios) - Relationship cases - Validation cases

Total Kappa Coverage: 258 scenarios (86 per function) covering sample sizes n=10 to n=2000

Stable Functions

agreement

Internal: agreement Purpose: Interrater reliability and agreement analysis When to use: Diagnostic concordance, QA studies, method comparison Methods: Kappa, ICC, Bland-Altman plots Test Data: 12 .omv files (binary, ordinal, continuous, multi-rater)

decision

Internal: decision Purpose: Diagnostic test performance analysis When to use: Evaluating tests, biomarkers, screening tools, clinical decision rules Metrics: Sensitivity, specificity, PPV, NPV, likelihood ratios Test Data: 16 .omv files

enhancedROC

Internal: enhancedROC Purpose: Advanced ROC analysis with optimal cutpoint selection When to use: Biomarker cutpoint optimization, ROC comparison, AUC analysis Test Data: 8 .omv files

jsurvival

Comprehensive survival analysis tools for clinical research.

Stable Functions

outcomeorganizer

Internal: outcomeorganizer Purpose: Calculate survival endpoints from raw event dates When to use: Preparing survival data from databases, calculating OS/PFS/DFS/RFS Test Data: 20 .omv files - Most comprehensive

timeinterval

Internal: timeinterval Purpose: Calculate time intervals between dates in various formats When to use: Treatment duration, follow-up time, date arithmetic Test Data: 24 .omv files - MOST comprehensive function

survival

Internal: survival Purpose: Comprehensive survival analysis with Cox regression When to use: Full survival analysis, multivariable models, hazard ratios Test Data: 9 .omv files

OncoPath

Specialized tools for pathology and oncology research.

Stable Functions

waterfall

Internal: waterfall Purpose: Treatment response waterfall plots (RECIST) When to use: Oncology trials, tumor burden change, identifying responders Test Data: 16 .omv files

swimmerplot

Internal: swimmerplot Purpose: Individual patient timeline visualization When to use: Clinical trial timelines, treatment sequences, patient journeys Test Data: 16 .omv files

ihcheterogeneity

Internal: ihcheterogeneity Purpose: IHC scoring heterogeneity and spatial variation analysis When to use: IHC quality control, intratumoral heterogeneity, multi-block sampling Test Data: 21 .omv files - 2nd most comprehensive

JJStatsPlot

Statistical visualization tools with automated statistics.

Stable Functions

jjcorrmat

Internal: jjcorrmat Purpose: Correlation matrices with significance and clustering When to use: Multiple biomarker relationships, laboratory panels, multivariate exploration Test Data: 6 .omv files

linechart

Internal: linechart Purpose: Line charts for longitudinal data When to use: Time series, biomarker trajectories, treatment response over time Test Data: 13 .omv files

Quick Reference Tables

Most Comprehensive Test Coverage

Functions with 15+ test data files:

Function Files Category Key Use
timeinterval 24 jsurvival Date calculations
ihcheterogeneity 21 OncoPath IHC heterogeneity
outcomeorganizer 20 jsurvival Survival endpoints
singlearm 18 jsurvival Phase II trials
nogoldstandard 18 meddecide Tests without gold standard
psychopdaROC 17 meddecide Cost-benefit ROC
survivalcont 17 jsurvival Cutpoint optimization

Functions by Clinical Domain

Survival Analysis: timeinterval (24), outcomeorganizer (20), singlearm (18), survivalcont (17)

Diagnostic Testing: nogoldstandard (18), psychopdaROC (17), decision (16), decisioncompare (14), kappasizeci (3)✨, kappasizefixedn (3)✨, kappasizepower (3)✨

Pathology: ihcheterogeneity (21), waterfall (16), swimmerplot (16), stagemigration (13)

Statistical Plots: hullplot (13), linechart (13), jjdotplotstats (8), jjhistostats (8)

Getting Help

How to Cite 

Balci S (2025). ClinicoPathJamoviModule: Clinicopathological Data Analysis.
R package version 0.0.31. https://github.com/sbalci/ClinicoPathJamoviModule

Note: This reference shows key functions. For the complete list of all 420+ functions, visit the full documentation.