num.id: Identify individuals in Joint model for clustered data

In frailtypack: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints

Identify individuals in Joint model for clustered data

Description

This is a special function used in addition to the cluster() function in the context of survival joint models for clustered data. This function identifies subject index. It is used on the right hand side of a 'frailtyPenal' formula. Using num.id() in a formula implies that a joint frailty model for clustered data is fitted (Rondeau et al. 2011).

Usage

num.id(x)

Arguments

x	A character or numeric variable which is supposed to indicate the variable identifying individuals

Value

No return value

References

V. Rondeau, J.P. Pignon, S. Michiels (2011). A joint model for the dependence between clustered times to tumour progression and deaths: A meta-analysis of chemotherapy in head and neck cancer. Statistical methods in medical research 897, 1-19.

See Also

frailtyPenal

Examples

data(readmission)
#-- here is generated cluster (5 clusters)
readmission <- transform(readmission,group=id%%5+1)

#-- exclusion all recurrent events --#
#--  to obtain framework of semi-competing risks --#
readmission2 <- subset(readmission, (t.start == 0 & event == 1) | event == 0)

joi.clus.gap <- frailtyPenal(Surv(time,event)~cluster(group)+
num.id(id)+dukes+charlson+sex+chemo+terminal(death),
formula.terminalEvent=~dukes+charlson+sex+chemo,
data=readmission2,recurrentAG=FALSE, n.knots=8,
kappa=c(1.e+10,1.e+10) ,Alpha="None")

frailtypack documentation built on June 27, 2024, 5:08 p.m.