slope: Identify variable associated with the random slope

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

Description

This is a special function used in the context of survival additive models. It identifies the variable which is in interaction with the random slope (v_i). Generally, this variable is the treatment variable. Using interaction() in a formula implies that an additive frailty model is fitted.

Usage

slope(x)

Arguments

x	A factor, a character or a numerical variable

Value

x	The variable in interaction with the random slope

Note

It is necessary to specify which variable is in interaction with the random slope, even if only one explanatory variable is included in the model.

See Also

additivePenal

Examples

## Not run: 

data(dataAdditive)

##-- Additive with one covariate --##

modAdd1cov <- additivePenal(Surv(t1,t2,event)~cluster(group)+var1+
slope(var1),data=dataAdditive,n.knots=8,kappa=10000,hazard="Splines")

##-- Additive with two covariates --##

set.seed(1234)
dataAdditive$var2 <- rbinom(nrow(dataAdditive),1,0.5)

modAdd2cov <- additivePenal(Surv(t1,t2,event)~cluster(group)+var1+
var2+slope(var1),data=dataAdditive,n.knots=8,kappa=10000,
hazard="Splines")

##-- Additive with 2 covariates and stratification --##

dataAdditive$var2 <- rbinom(nrow(dataAdditive),1,0.5)

modAddstrat <- additivePenal(Surv(t1,t2,event)~cluster(group)+
strata(var2)+var1+slope(var1),data=dataAdditive,n.knots=8,
kappa=c(10000,10000),hazard="Splines")


## End(Not run)

socale/frailtypack documentation built on June 15, 2021, 3:37 a.m.