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markovMSM
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Download and install markovMSM package within the R console
Install from CRAN:
install.packages("markovMSM")
Install from Github:
library("remotes")
install_github("cran/markovMSM")
Install by package version:
library("remotes")
install_version("markovMSM", "0.1.3")
Attach the package and use:
library("markovMSM")
Maintained by
Gustavo Soutinho
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-23
Latest Update: 2023-02-15
Description:
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) and Titman AC, Putter H
(2020) ).
How to cite:
Gustavo Soutinho (2021). markovMSM: Methods for Checking the Markov Condition in Multi-State Survival Data. R package version 0.1.3, https://cran.r-project.org/web/packages/markovMSM. Accessed 22 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for markovMSM
Functions, R codes and Examples using
the markovMSM R package
Some associated functions: AUC.test . LR.test . PHM.test . colonMSM . ebmt4 . eventsMSM . plot.markovMSM . prepMSM . print.markovMSM . prothr . summary.markovMSM . transMatMSM .
Some associated R codes: AUC.test.R . LMAJ2.R . LR.test.R . MarkovTest.R . NAfix2.R . PHM.test.R . eventsMSM.R . msfit2.R . optimal_weights_matrix.R . optimal_weights_multiple.R . plot.markovMSM.R . prepMSM.R . print.markovMSM.R . summary.markovMSM.R . to-trans2.R . transMatMSM.R . Full markovMSM package functions and examples
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