Function Reference Guide
ClinicoPath Team
2026-01-08
Source:vignettes/function-reference.Rmd
function-reference.RmdClinicoPathJamoviModule Function Reference
Total Functions: 420+ 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 catalogs all 420+ analysis functions in ClinicoPathJamoviModule 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
Quick Navigation
- ClinicoPathDescriptives - Descriptive statistics, data quality
- JJStatsPlot - Statistical visualizations
- OncoPath - Pathology and oncology analyses
- jsurvival - Survival analysis tools
- meddecide - Diagnostic test evaluation, decision analysis
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
- Documentation: www.serdarbalci.com/ClinicoPathJamoviModule
- GitHub Issues: Report bugs or request features
- Test Data: Browse all .omv files
-
Complete Catalog: See
vignette("test-data-catalog")for all 945 test datasets
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.