dualic: Simulated dual-censored data from an illness-death process
Description
Data from a Markov illness-death process with interval-censored
progression times, simulated according to the initial scenario
described in Boruvka and Cook (2014).
Format
A data frame with 723 observations on the following 7 variables.
id-
subject identifier.
from-
originating state index with
0 denoting the initial state,
1 the intermediate state, 2 the terminal state and
NA an unknown state.
to-
subsequent state index.
start-
left endpoint of the time interval at which the subject is known
to be at risk for a transition between state
from and state
to.
stop-
right endpoint of the at-risk interval.
status-
indicator that a transition between state
from and state
to was observed at stop.
z-
a binary covariate.
References
Boruvka, A. and Cook, R. J. (2014)
Sieve estimation in a Markov illness-death process under dual censoring.