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.
simfitted.msm(x, drop.absorb = TRUE, drop.pci.imp = TRUE)A dataset with variables as described in simmulti.msm.
A fitted multi-state model object as returned by msm.
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.
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.
C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk
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.
simmulti.msm, sim.msm,
pearson.msm, msm.