msm (version 1.2)

simfitted.msm: Simulate from a Markov model fitted using msm

Description

Simulate a dataset from a Markov model fitted using msm, using the maximum likelihood estimates as parameters, and the same observation times as in the original data.

Usage

simfitted.msm(x, drop.absorb=TRUE, drop.pci.imp=TRUE)

Arguments

x

A fitted multi-state model object as returned by msm.

drop.absorb

Should repeated observations in an absorbing state be omitted. Use the default of TRUE to avoid warnings when using the simulated dataset for further msm fits. Or set to FALSE

drop.pci.imp

In time-inhomogeneous models fitted using the pci option to msm, censored observations are inserted into the data by msm at the times where

Value

• A dataset with variables as described in simmulti.msm.

concept

Simulation

Details

This function is a wrapper around simmulti.msm, and only simulates panel-observed data. To generate datasets with the exact times of transition, use the lower-level sim.msm.

Markov models with misclassified states fitted through the ematrix option to msm are supported, but not general hidden Markov models with hmodel. For misclassification models, this function includes misclassification in the simulated states. This function is used for parametric bootstrapping to estimate the null distribution of the test statistic in pearson.msm.

See Also

simmulti.msm, sim.msm, pearson.msm, msm.