pmatrix.msm {msm}R Documentation

Transition probability matrix

Description

Extract the estimated transition probability matrix from a fitted multi-state model for a given time interval, at a given set of covariate values.

Usage

pmatrix.msm(x, t, covariates="mean")

Arguments

x A fitted multi-state model, as returned by msm.
t The time interval to estimate the transition probabilities for.
covariates The covariate values at which to estimate the transition probabilities. This can either be:

the string "mean", denoting the means of the covariates in the data (this is the default),

the number 0, indicating that all the covariates should be set to zero,

or a list of values, with optional names. For example
list (60, 1)
where the order of the list follows the order of the covariates originally given in the model formula, or a named list,
list (age = 60, sex = 1)

Details

For a continuous-time homogeneous Markov process with transition intensity matrix Q, the probability of occupying state s at time u + t conditional on occupying state r at time u is given by the (r,s) entry of the matrix P(t) = exp(tQ).

For non-homogeneous processes, where covariates and hence the transition intensity matrix vary but are piecewise-constant within the time interval [u, u+t], the function pmatrix.piecewise.msm can be used.

Value

The matrix of estimated transition probabilities P(t) in the given time. Rows correspond to "from-state" and columns to "to-state".

Author(s)

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

See Also

qmatrix.msm, pmatrix.piecewise.msm


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