Package: mmbcv 0.3.0

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. 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.

Authors:Can Meng [aut, cre], Denise Esserman [aut], Fan Li [aut], Erich Greene [aut]

mmbcv_0.3.0.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
mmbcv/json (API)

# Install 'mmbcv' in R:
install.packages('mmbcv', repos = c('https://mengcan47.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • msdat3 - Clustered multistate simulated dataset

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 443 downloads 2 exports 0 dependencies

Last updated from:7ba5e94a59. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK148
linux-release-x86_64OK126
macos-release-arm64OK153
macos-oldrel-arm64OK133
windows-develOK73
windows-releaseOK69
windows-oldrelOK73
wasm-releaseOK91

Exports:MMBCVsubset_by_transition

Dependencies:

mmbcv: Bias-corrected sandwich variance for clustered multistate Cox models

Rendered frommmbcv-intro.Rmdusingknitr::rmarkdownon May 31 2026.

Last update: 2026-03-31
Started: 2026-03-31