semicmprskcoxmsm: Use Inverse Probability Weighting to Estimate Treatment Effect for Semi Competing Risks Data

Use inverse probability weighting methods to estimate treatment effect under marginal structure model (MSM) for the transition hazard of semi competing risk data, i.e. illness death model. We implement two specific such models, the usual Markov illness death structural model and the general Markov illness death structural model. We also provide the predicted three risks functions from the marginal structure models. Zhang, Y. and Xu, R. (2022) <doi:10.48550/arXiv.2204.10426>.

Version: 0.2.0
Imports: ggplot2, survival, stats, twang, graphics, fastGHQuad, Rcpp
Suggests: knitr, rmarkdown
Published: 2022-04-29
Author: Yiran Zhang
Maintainer: Yiran Zhang <yiz038 at health.ucsd.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: semicmprskcoxmsm results

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Reference manual: semicmprskcoxmsm.pdf

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Package source: semicmprskcoxmsm_0.2.0.tar.gz
Windows binaries: r-devel: semicmprskcoxmsm_0.2.0.zip, r-release: semicmprskcoxmsm_0.2.0.zip, r-oldrel: semicmprskcoxmsm_0.2.0.zip
macOS binaries: r-release (arm64): semicmprskcoxmsm_0.2.0.tgz, r-oldrel (arm64): semicmprskcoxmsm_0.2.0.tgz, r-release (x86_64): semicmprskcoxmsm_0.2.0.tgz
Old sources: semicmprskcoxmsm archive

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