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.

## 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`

if exactly the same number of observations as the original data are needed.- 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 the intensity changes, but dropped by default when simulating from the fitted model using this function. Set this argument to`FALSE`

to keep these observations and the corresponding indicator variable.

## Value

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

.

## 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`

.

## Author

C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk