slope {frailtypack} | R Documentation |
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.
slope(x)
x |
A factor, a character or a numerical variable |
x |
The variable in interaction with the random slope |
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
, print.additivePenal
,
plot.additivePenal
, summary.additivePenal
## Not run: library(frailtypack) data(dataAdditive) # Additive with one covariate # modAdd1cov<-additivePenal(Surv(t1,t2,event)~cluster(group)+var1+ slope(var1),data=dataAdditive,n.knots=8,kappa1=10000) # Additive with two covariates # set.seed(1234) dataAdditive$var2<-rbinom(nrow(dataAdditive),1,0.5) modAdd2cov<-additivePenal(Surv(t1,t2,event)~cluster(group)+var1+var2+ slope(var1),data=dataAdditive,n.knots=8,kappa1=10000) # Additive with 2 covariates and stratification # dataAdditive$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,kappa1=10000,kappa2=10000) ## End(Not run)