mmbcv: Multistate Model Bias-Corrected Robust Variance

Computes robust and bias-corrected sandwich variance estimators for multi-state Cox models with clustered time-to-event data. Also provides Wald tests for heterogeneity, generalized least-squares linear trends, and order-restricted trends among transition-specific coefficients. The methodology extends the marginal Cox model bias-correction framework of Wang et al. (2023) <doi:10.1002/bimj.202200113> to the multi-state setting.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Suggests: knitr, rmarkdown, survival, testthat (≥ 3.0.0)
Published: 2026-07-22
DOI: 10.32614/CRAN.package.mmbcv
Author: Can Meng [aut, cre], Denise Esserman [aut], Fan Li [aut], Erich Greene [aut]
Maintainer: Can Meng <can.meng at yale.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: NEWS
CRAN checks: mmbcv results

Documentation:

Reference manual: mmbcv.html , mmbcv.pdf
Vignettes: mmbcv: Bias-corrected sandwich variance for clustered multistate Cox models (source, R code)

Downloads:

Package source: mmbcv_1.0.0.tar.gz
Windows binaries: r-devel: mmbcv_0.3.0.zip, r-release: mmbcv_0.3.0.zip, r-oldrel: mmbcv_0.3.0.zip
macOS binaries: r-release (arm64): mmbcv_1.0.0.tgz, r-oldrel (arm64): mmbcv_1.0.0.tgz, r-release (x86_64): mmbcv_1.0.0.tgz, r-oldrel (x86_64): mmbcv_1.0.0.tgz
Old sources: mmbcv archive

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