Methods for Checking the Markov Condition in Multi-State Survival Data
Overview
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).
- Further information on the length time for computational executation of global and local tests of AUCtest function.
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Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- WARNING12 OK, 1 WARNING2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 12
- Examples that run
- 83%10 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 91%
- Return-value docs
- 100%
- Help pages citing references
- 75%
Downloads
Dependencies
Installing markovMSM adds 5 packages (3 with compiled code, 8.5 MB of source tarballs). Heaviest: data.table 5.7 MB, viridisLite 1.2 MB, mstate 900 KB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2021-11-23
- Total releases
- 4 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 52 KB / 3 files
- Download size
- 88 KB
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