modMStates: Simulation and Estimation of Continuous-Time Multi-State Markov
Models for Panel Data
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>.
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