pmatrix.msm {msm} | R Documentation |
Extract the estimated transition probability matrix from a fitted multi-state model for a given time interval, at a given set of covariate values.
pmatrix.msm(x, t, covariates="mean")
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)
|
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.
The matrix of estimated transition probabilities P(t) in the given time. Rows correspond to "from-state" and columns to "to-state".
C. H. Jackson chris.jackson@imperial.ac.uk
qmatrix.msm
, pmatrix.piecewise.msm