# slope: Identify variable associated with the random slope In 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

 `1` ```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.

`additivePenal`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```## 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) ```