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modMStates  

Simulation and Estimation of Continuous-Time Multi-State Markov Models for Panel Data
View on CRAN: Click here


Download and install modMStates package within the R console
Install from CRAN:
install.packages("modMStates")

Install from Github:
library("remotes")
install_github("cran/modMStates")

Install by package version:
library("remotes")
install_version("modMStates", "0.0.1")



Attach the package and use:
library("modMStates")
Maintained by
Atanu Bhattacharjee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-03
Latest Update: 2026-09-03
Description:
A higher-level interface to continuous-time Markov multi-state models for panel (interval-censored) data. Seven canonical clinical process structures are supplied with structurally valid generator matrices, so that transition matrices and starting values need not be constructed by hand. Panel data can be simulated from exact trajectories under regular or irregular observation schedules, with optional exactly observed absorption times and optional Weibull holding times for assessing the Markov assumption. A single fitting call validates the input against the assumed structure and returns the estimated generator with confidence intervals, mean sojourn times, transition probability matrices and observed transition counts, together with the optimiser's convergence code. A Monte Carlo driver reports Monte Carlo standard errors alongside bias, root mean squared error and interval coverage. Likelihood evaluation is delegated to 'msm' (Jackson, 2011, <doi:10.18637/jss.v038.i08>); the panel-data likelihood is that of Kalbfleisch and Lawless (1985) <doi:10.1080/01621459.1985.10478195>.
How to cite:
Atanu Bhattacharjee (2026). modMStates: Simulation and Estimation of Continuous-Time Multi-State Markov Models for Panel Data. R package version 0.0.1, https://cran.r-project.org/web/packages/modMStates. Accessed 24 Oct. 2026.
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