Learn R Programming

mets (version 1.2)

twin.clustertrunc: Estimation of twostage model with cluster truncation in bivariate situation

Description

Estimation of twostage model with cluster truncation in bivariate situation

Usage

twin.clustertrunc(survformula, data = sys.parent(), theta.des = NULL,
  clusters = NULL, Nit = 10, final.fitting = FALSE, ...)

Arguments

survformula
Formula with survival model aalen or cox.aalen, some limitiation on model specification due to call of fast.reshape (so for example interactions and * and : do not work here, expand prior to call)
data
Data frame
theta.des
design for dependence parameters in two-stage model
clusters
clustering variable for twins
Nit
number of iteration
final.fitting
TRUE to do final estimation with SE and ... arguments for marginal models
...
Additional arguments to lower level functions

Examples

Run this code
library("timereg")
data(diabetes)
v <- diabetes$time*runif(nrow(diabetes))*rbinom(nrow(diabetes),1,0.5)
diabetes$v <- v

aout <- twin.clustertrunc(Surv(v,time,status)~1+treat+adult,
		 data=diabetes,clusters="id")
aout$two        ## twostage output
par(mfrow=c(2,2))
plot(aout$marg) ## marginal model output

out <- twin.clustertrunc(Surv(v,time,status)~1+prop(treat)+prop(adult),
		 data=diabetes,clusters="id")
out$two        ## twostage output
plot(out$marg) ## marginal model output

Run the code above in your browser using DataLab