View source: R/twin.clustertrunc.r
twin.clustertrunc | R Documentation |
Estimation of twostage model with cluster truncation in bivariate situation
twin.clustertrunc( survformula, data = parent.frame(), theta.des = NULL, clusters = NULL, var.link = 1, Nit = 10, final.fitting = FALSE, ... )
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 |
var.link |
exp link for theta |
Nit |
number of iteration |
final.fitting |
TRUE to do final estimation with SE and ... arguments for marginal models |
... |
Additional arguments to lower level functions |
Thomas Scheike
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
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