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markovMSM: Methods for Checking the Markov Condition in Multi-State Survival Data

The inference in multi-state models is traditionally performed under a Markov assumption that claims that past and future of the process are independent given the present state. In this package, we consider tests of the Markov assumption that are applicable to general multi-state models. Three approaches using existing methodology are considered: a simple method based on including covariates depending on the history in Cox models for the transition intensities; methods based on measuring the discrepancy of the non-Markov estimators of the transition probabilities to the Markov Aalen-Johansen estimators; and, finally, methods that were developed by considering summaries from families of log-rank statistics where patients are grouped by the state occupied of the process at a particular time point (see Soutinho G, Meira-Machado L (2021) <doi:10.1007/s00180-021-01139-7> and Titman AC, Putter H (2020) <doi:10.1093/biostatistics/kxaa030>).

Version: 0.1.3
Depends: R (≥ 3.5.0)
Imports: survival, mstate
Suggests: rmarkdown, knitr, doParallel, devtools, bibtex, testthat
Published: 2023-02-15
DOI: 10.32614/CRAN.package.markovMSM
Author: Gustavo Soutinho ORCID iD [aut, cre], Luis Meira-Machado ORCID iD [aut]
Maintainer: Gustavo Soutinho <gustavosoutinho at sapo.pt>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: markovMSM results

Documentation:

Reference manual: markovMSM.pdf
Vignettes: markovMSM: An R package for checking the Markov condition in multi-state survival data

Downloads:

Package source: markovMSM_0.1.3.tar.gz
Windows binaries: r-devel: markovMSM_0.1.3.zip, r-release: markovMSM_0.1.3.zip, r-oldrel: markovMSM_0.1.3.zip
macOS binaries: r-release (arm64): markovMSM_0.1.3.tgz, r-oldrel (arm64): markovMSM_0.1.3.tgz, r-release (x86_64): markovMSM_0.1.3.tgz, r-oldrel (x86_64): markovMSM_0.1.3.tgz
Old sources: markovMSM archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.