pmatrix.msm | R Documentation |
Extract the estimated transition probability matrix from a fitted continuous-time multi-state model for a given time interval, at a given set of covariate values.
pmatrix.msm(
x = NULL,
t = 1,
t1 = 0,
covariates = "mean",
ci = c("none", "normal", "bootstrap"),
cl = 0.95,
B = 1000,
cores = NULL,
qmatrix = NULL,
...
)
x |
A fitted multi-state model, as returned by |
t |
The time interval to estimate the transition probabilities for, by default one unit. |
t1 |
The starting time of the interval. Used for models |
covariates |
The covariate values at which to estimate the transition
probabilities. This can either be: the string the number or a list of values, with optional names. For example
where the order of the list follows the order of the covariates originally given in the model formula, or a named list,
If some covariates are specified but not others, the missing ones default to zero. For time-inhomogeneous models fitted using the For time-inhomogeneous models fitted "by hand" by using a time-dependent
covariate in the |
ci |
If If If |
cl |
Width of the symmetric confidence interval, relative to 1. |
B |
Number of bootstrap replicates, or number of normal simulations from the distribution of the MLEs |
cores |
Number of cores to use for bootstrapping using parallel
processing. See |
qmatrix |
A transition intensity matrix. Either this or a fitted model
|
... |
Optional arguments to be passed to |
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)
, where
\exp()
is the matrix exponential.
For non-homogeneous processes, where covariates and hence the transition
intensity matrix Q
are piecewise-constant in time, the transition
probability matrix is calculated as a product of matrices over a series of
intervals, as explained in pmatrix.piecewise.msm
.
The pmatrix.piecewise.msm
function is only necessary for
models fitted using a time-dependent covariate in the covariates
argument to msm
. For time-inhomogeneous models fitted using
"pci", pmatrix.msm
can be used, with arguments t
and
t1
, to calculate transition probabilities over any time period.
The matrix of estimated transition probabilities P(t)
in the
given time. Rows correspond to "from-state" and columns to "to-state".
Or if ci="normal"
or ci="bootstrap"
, pmatrix.msm
returns a list with components estimates
and ci
, where
estimates
is the matrix of estimated transition probabilities, and
ci
is a list of two matrices containing the upper and lower
confidence limits.
C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk.
Mandel, M. (2013). "Simulation based confidence intervals for functions with complicated derivatives." The American Statistician 67(2):76-81
qmatrix.msm
, pmatrix.piecewise.msm
,
boot.msm
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