dataJoint {frailtypack}R Documentation

Simulated data with recurrent events and informative terminal event

Description

This contains simulated data with recurrent events and time until last follow-up that is related to the recurrent process. This data set is useful to illustrate how to fit a joint model where the censoring mechanism is informative about the recurring process. This database combines different observations for each subject (sample size=500, number of lines=1053 so in average more than two recurrent events per subject). The right-censored case is treated only and the calendar timescale representation is used with delayed entry. Exponential death times and recurring times are generated using a gamma frailty model. The common frailty term is iid Γ(2,2) and α, the coefficient associated with the frailty term in the death time hazard function, is set at 0. The right-censoring variable is set at 0.8 and the two covariates are generated from a Bernoulli distribution (p=0.5).

Usage

data(dataJoint)

Format

This data frame contains the following columns:

id
identification variable (ex: subject number)
time.entry
start of interval (0 or previous recurrence time)
time.end
end of interval (recurrence or censoring time)
status
censoring status for recurrent events (1:event, 0: censored or dead
status.terminal
censoring status for terminal events (0:alive, 1:death)
var1
dichotomous covariate (0,1)
var2
dichotomous covariate (0,1)

Source

V. Rondeau, S. Mathoulin-Pellissier, H. Jacqmin-Gadda, V. Brouste, P. Soubeyran (2007). Joint frailty models for recurring events and death using maximum penalized likelihood estimation:application on cancer events. Biostatistics, 8,4, 708-721.

See Also

frailtyPenal for Joint frailty models


[Package frailtypack version 2.2-9.5 Index]