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forestsearch - Exploratory Subgroup Identification in Survival and GLM Outcomes

Implements statistical methods for exploratory subgroup identification in clinical trials. Provides tools for identifying patient subgroups with differential treatment effects using machine learning approaches including Generalized Random Forests (GRF), LASSO regularization, and exhaustive combinatorial search algorithms. Supports survival endpoints (Cox proportional hazards), binary outcomes (log odds ratio, log relative risk, risk difference), continuous outcomes (mean difference), and count / rate outcomes (log incidence rate ratio via Poisson, quasi-Poisson, or negative-binomial GLMs with optional person-time offset). Features bootstrap bias correction using infinitesimal jackknife methods to address selection bias in post-hoc analyses. Designed for clinical researchers conducting exploratory subgroup analyses in randomized controlled trials, particularly for multi-regional clinical trials (MRCT) requiring regional consistency evaluation. Methods are described in Leon et al. (2024) <doi:10.1002/sim.10163>. Post-selection inference for the identified subgroup follows León and Anderson (2026) <doi:10.48550/arXiv.2609.38361>. The search methodology is given in León and Anderson (2026) <doi:10.48550/arXiv.2610.28379>.

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heterogeneous-treatment-effectspost-selection-inferencesubgroupsquarto

7.76 score 3 stars 808 scripts 415 downloads

weightedsurv - Survival Analysis with Subject-Specific (Case Weights) and Time-Dependent Weighting

Provides survival analysis functions with support for time-dependent and subject-specific (e.g., propensity score) weighting. Implements weighted estimation for Cox models, Kaplan-Meier survival curves, and treatment differences with point-wise and simultaneous confidence bands. Includes restricted mean survival time (RMST) comparisons evaluated across all potential truncation times with both point-wise and simultaneous confidence bands. See Cole, S. R. & Hernán, M. A. (2004) <doi:10.1016/j.cmpb.2003.10.004> for methodological background.

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kaplan-meierrmstweighted-coxwlr

5.94 score 5 stars 1 dependents 29 scripts 371 downloads