Package: uddbart 0.2.0

uddbart: Unified Dynamic Deep 'BART' for Interval-Censored Survival

Implements U-DDBART-IC, a unified Bayesian workflow for dynamic risk prediction from irregular longitudinal biomarkers when event times are interval-censored between clinical visits. The package turns long-format biomarker histories and patient-level interval endpoints L, R, C and delta into a discrete-time follow-up grid, summarises each landmark history with nine interpretable trajectory features (current, baseline and previous biomarker values, last visit gap, local slope, cumulative decline, best value, elapsed time and visit count), fits discrete-time interval hazards using optional logit-link Bayesian additive regression trees, a generalized linear model fallback, or a lightweight variational approximation, accumulates survival from the discrete-time product, and evaluates the interval-censored likelihood. Fitted models return landmark risk predictions over user-specified horizons with posterior or bootstrap uncertainty by evaluating survival ratios across fitted hazard draws. Utilities are provided for simulation, staged model fitting, plotting and summarising dynamic risk curves, IPCW Brier scores, cumulative/dynamic time-dependent area under the curve, calibration tables, and an anonymised chronic myeloid leukaemia molecular-monitoring example data set.

Authors:Xulin Pan [aut, cre]