Semi-Parametric Association Surfaces for Joint Longitudinal-Survival Models
Overview
Implements interpretable multi-biomarker fusion in joint longitudinal-survival models via semi-parametric association surfaces. Provides a two-stage estimation framework where Stage 1 fits mixed-effects longitudinal models and extracts Best Linear Unbiased Predictors ('BLUP's), and Stage 2 fits transition-specific penalized Cox models with tensor-product spline surfaces linking latent biomarker summaries to transition hazards. Supports multi-state disease processes with transition-specific surfaces, Restricted Maximum Likelihood ('REML') smoothing parameter selection, effective degrees of freedom ('EDF') diagnostics, dynamic prediction of transition probabilities, and three interpretability visualizations (surface plots, contour heatmaps, marginal effect slices). Methods are described in Bhattacharjee (2025, under review).
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 16includes a package overview page
- Examples that run
- 33%1 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 25%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 13%
Downloads
Dependencies
Installing jmSurface adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-02-25 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-02-25
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.0.0
- Download size
- 517 KB
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