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.