prob.exceed.recurrent: Estimation of probability of more that k events for recurrent...

In kkholst/mets: Analysis of Multivariate Event Times

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(hfaction_cpx12)
dtable(hfaction_cpx12,~status)

oo <- prob.exceed.recurrent(Event(entry,time,status)~cluster(id),
        hfaction_cpx12,cause=1,death.code=2)
plot(oo)

kkholst/mets documentation built on March 5, 2025, 2:39 p.m.