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jmSurface

Semi-Parametric Association Surfaces for Joint Longitudinal-Survival Models

v0.1.0 · Feb 25, 2026 · GPL (>= 3)

Description

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).

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies nlme survival mgcv jmSurface

Version History

1 tracked
new 0.1.0 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Feb 25, 2026. Releases before tracking aren’t shown.