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mets (version 0.1-12)

ClaytonOakes: Clayton-Oakes model with piece-wise constant hazards

Description

Clayton-Oakes frailty model

Usage

ClaytonOakes(formula, data = parent.frame(), cluster,
    var.formula = ~1, cuts = NULL, type = "piecewise",
    start, control = list(), var.invlink = exp, ...)

Arguments

formula
formula specifying the marginal proportional (piecewise constant) hazard structure with the right-hand-side being a survival object (Surv) specifying the entry time (optional), the follow-up time, and event/censoring status at follow-up. The clust
data
Data frame
cluster
Variable defining the clustering (if not given in the formula)
var.formula
Formula specifying the variance component structure (if not given via the cluster special function in the formula) using a linear model with log-link.
cuts
Cut points defining the piecewise constant hazard
type
when equal to two.stage, the Clayton-Oakes-Glidden estimator will be calculated via the timereg package
start
Optional starting values
control
Control parameters to the optimization routine
var.invlink
Inverse link function for variance structure model
...
Additional arguments

Examples

Run this code
set.seed(1)
d <- subset(simClaytonOakes(500,4,2,1,stoptime=2,left=2),!truncated)
e <- ClaytonOakes(Surv(lefttime,time,status)~x1+cluster(~1,cluster),cuts=c(0,0.5,1,2),data=d)
e

d2 <- simClaytonOakes(500,4,2,1,stoptime=2,left=0)
d$z <- rep(1,nrow(d)); d$z[d$cluster%in%sample(d$cluster,100)] <- 0
ts <- ClaytonOakes(Surv(time,status)~prop(x1)+cluster(~1,cluster),data=d,type="two.stage") ## Cox Proportional Hazards model
ts2 <- ClaytonOakes(Surv(time,status)~x1+cluster(~1+factor(z),cluster),data=d,type="two.stage") ## Aalen's Additive model
e2 <- ClaytonOakes(Surv(time,status)~x1+cluster(~-1+factor(z),cluster),cuts=c(0,0.5,1,2),data=d)
e2
plot(ts)
plot(e2,add=TRUE)
e3 <- ClaytonOakes(Surv(time,status)~x1+cluster(~1,cluster),cuts=c(0,0.5,1,2),data=d,var.invlink=identity)
e3

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