prob.exceed.recurrent {mets} | R Documentation |
Estimation of probability of more that k events for recurrent events process
Description
Estimation of probability of more that k events for recurrent events process where there is terminal event, based on this also estimate of variance of recurrent events. The estimator is based on cumulative incidence of exceeding "k" events. In contrast the probability of exceeding k events can also be computed as a counting process integral, and this is implemented in prob.exceedRecurrent
Usage
prob.exceed.recurrent(
formula,
data,
cause = 1,
death.code = 2,
cens.code = 0,
exceed = NULL,
marks = NULL,
cifmets = TRUE,
all.cifs = FALSE,
...
)
Arguments
formula |
formula |
data |
data-frame |
cause |
of interest |
death.code |
for status |
cens.code |
censoring codes |
exceed |
values (if not given then all observed values) |
marks |
may be give for jump-times and then exceed values needs to be specified |
cifmets |
if true uses cif of mets package rather than prodlim |
all.cifs |
if true then returns list of all fitted objects in cif.exceed |
... |
Additional arguments to lower level funtions |
Author(s)
Thomas Scheike
References
Scheike, Eriksson, Tribler (2019) The mean, variance and correlation for bivariate recurrent events with a terminal event, JRSS-C
Examples
data(hfactioncpx12)
dtable(hfactioncpx12,~status)
oo <- prob.exceed.recurrent(Event(entry,time,status)~cluster(id),
hfactioncpx12,cause=1,death.code=2)
plot(oo)