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DRsurvCRT

0.0.1

Doubly-Robust Estimation for Survival Outcomes in Cluster-Randomized Trials

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Overview

About
Maintained by Xi FangFirst published 2025-12-301 releasesCRAN page ↗

Cluster-randomized trials (CRTs) assign treatment to groups rather than individuals, so valid analyses must distinguish cluster-level and individual-level effects and define estimands within a potential-outcomes framework. This package supports right-censored survival outcomes for both single-state (binary) and multi-state settings. For single-state outcomes, it provides estimands based on stage-specific survival contrasts (SPCE) and restricted mean survival time (RMST). For multi-state outcomes, it provides SPCE as well as a generalized win-based restricted mean time-in-favor estimand (RMT-IF). The package implements doubly robust estimators that accommodate covariate-dependent censoring and remain consistent if either the outcome model or the censoring model is correctly specified. Users can choose marginal Cox or gamma-frailty Cox working models for nuisance estimation, and inference is supported via leave-one-cluster-out jackknife variance and confidence interval estimation. Methods are described in Fang et al. (2025) "Estimands and doubly robust estimation for cluster-randomized trials with survival outcomes" doi:10.48550/arXiv.2510.08438.

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  • ERROR2026-04-18
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  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

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Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5
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Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.0.1Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-12-30
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 3.5
Bundled data
61 KB / 2 files
Download size
93 KB
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not tracked yet
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