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=1, covariates="mean", ci.boot=FALSE, cl=0.95, B=500)

Arguments

x A fitted multi-state model, as returned by msm.
t The time interval to estimate the transition probabilities for, by default one unit.
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)
ci.boot Calculate a bootstrap confidence interval. This is usually time-consuming, and disabled by default. See boot.msm for more details of bootstrapping in msm.
cl Width of the symmetric confidence interval
B Number of bootstrap replicates

Details

For a continuous-time homogeneous Markov process with transition intensity matrix Q, the probability of occupying state s at time u + t conditionally 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 are time-dependent, 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, boot.msm


[Package msm version 0.7.1 Index]