- x
A fitted multi-state model, as returned by
msm
. This should be a non-homogeneous model, whose
transition intensity matrix depends on a time-dependent covariate.
- t1
The start of the time interval to estimate the transition probabilities for.
- t2
The end of the time interval to estimate the transition probabilities
for.
- times
Cut points at which the transition intensity matrix changes.
- covariates
A list with number of components one greater than the length of
times
. Each component of the list is specified in the same
way as the covariates
argument to pmatrix.msm
.
The components correspond to the covariate values in the intervals
(t1, times[1]], (times[1], times[2]], ...,
(times[length(times)], t2]
(assuming that all elements of times
are in the interval
(t1, t2)
).
- ci
If "normal"
, then calculate a confidence interval for
the transition probabilities by simulating B
random vectors
from the asymptotic multivariate normal distribution implied by the
maximum likelihood estimates (and covariance matrix) of the log
transition intensities and covariate effects, then calculating the
resulting transition probability matrix for each replicate.
If "bootstrap"
then calculate a confidence interval by
non-parametric bootstrap refitting. This is 1-2 orders of magnitude
slower than the "normal"
method, but is expected to be more
accurate. See boot.msm
for more details of
bootstrapping in msm.
If "none"
(the default) then no confidence interval is
calculated.
- 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 boot.msm
for more details.
- qlist
A list of transition intensity matrices, of length one
greater than the length of times
. Either this or
a fitted model x
must be supplied. No confidence intervals
are available if (just) qlist
is supplied.
- ...
Optional arguments to be passed to MatrixExp
to
control the method of computing the matrix exponential.