msm.summary {msm}R Documentation

Summarise a fitted multi-state model

Description

Summary method for fitted msm models. Produces a table of observed and expected state prevalences for each time. For models with covariates, prints hazard ratios with confidence intervals for covariate effects.

Usage

## S3 method for class 'msm':
summary(object, times=NULL, timezero=NULL, initstates=NULL,
covariates="mean", misccovariates="mean", hazard.scale=1, ...)

Arguments

object A fitted multi-state model object, as returned by msm.
times A sequence of times at which to compare observed and expected prevalences of each state. Defaults to seq(min(times), max(times), (max(times) - min(times))/10).
timezero Initial time of the Markov process. Expected values are forecasted from here. Defaults to the minimum of the observation times given in the data.
initstates Optional vector of the same length as the number of states. Gives the numbers of individuals occupying each state at timezero. The default is that all individuals are in state 1.
covariates Covariate values for which to forecast expected state occupancy. See qmatrix.msm. Defaults to the mean values of the covariates in the data set.
misccovariates (Misclassification models only) Values of covariates on the misclassification probability matrix for which to forecast expected state occupancy. Defaults to the mean values of the covariates in the data set.
hazard.scale Vector with same elements as number of covariates on transition rates. Corresponds to the increase in each covariate used to calculate its hazard ratio. Defaults to all 1.
... further arguments passed to or from other methods

Value

A list of class summary.msm, with components:

prevalences Output from prevalence.msm
hazard Output from hazard.msm
hazard.scale Value of the hazard.scale argument

Note

The prevalence table is not available if the data were specified in fromto format in the call to msm. Expected prevalences only make sense for processes where all individuals start at a common time.

Author(s)

C. H. Jackson chris.jackson@imperial.ac.uk

See Also

msm, print.summary.msm prevalence.msm, hazard.msm


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