ipw2: Inverse Probability of Censoring Weights

In mets: Analysis of Multivariate Event Times

Inverse Probability of Censoring Weights

Description

Internal function. Calculates Inverse Probability of Censoring and Truncation Weights and adds them to a data.frame

Usage

ipw2(
  data,
  times = NULL,
  entrytime = NULL,
  time = "time",
  cause = "cause",
  same.cens = FALSE,
  cluster = NULL,
  pairs = FALSE,
  strata = NULL,
  obs.only = TRUE,
  cens.formula = NULL,
  cens.code = 0,
  pair.cweight = "pcw",
  pair.tweight = "ptw",
  pair.weight = "weights",
  cname = "cweights",
  tname = "tweights",
  weight.name = "indi.weights",
  prec.factor = 100,
  ...
)

Arguments

data	data frame
times	possible time argument for speciying a maximum value of time tau=max(times), to specify when things are considered censored or not.
entrytime	nam of entry-time for truncation.
time	name of time variable on data frame.
cause	name of cause indicator on data frame.
same.cens	For clustered data, should same censoring be assumed and same truncation (bivariate probability calculated as mininum of the marginal probabilities)
cluster	name of clustering variable
pairs	For paired data (e.g. twins) only the complete pairs are returned (With pairs=TRUE)
strata	name of strata variable to get weights stratified.
obs.only	Return data with uncensored observations only
cens.formula	model for Cox models for truncation and right censoring times.
cens.code	censoring.code
pair.cweight	Name of weight variable in the new data.frame for right censorig of pairs
pair.tweight	Name of weight variable in the new data.frame for left truncation of pairs
pair.weight	Name of weight variable in the new data.frame for right censoring and left truncation of pairs
cname	Name of weight variable in the new data.frame for right censoring of individuals
tname	Name of weight variable in the new data.frame for left truncation of individuals
weight.name	Name of weight variable in the new data.frame for right censoring and left truncation of individuals
prec.factor	To let tied censoring and truncation times come after the death times.
...	Additional arguments to censoring model

Author(s)

Thomas Scheike

Examples

library("timereg")
set.seed(1)
d <- simnordic.random(5000,delayed=TRUE,ptrunc=0.7,
      cordz=0.5,cormz=2,lam0=0.3,country=FALSE)
d$strata <- as.numeric(d$country)+(d$zyg=="MZ")*4
times <- seq(60,100,by=10)
c1 <- timereg::comp.risk(Event(time,cause)~1+cluster(id),data=d,cause=1,
	model="fg",times=times,max.clust=NULL,n.sim=0)
mm=model.matrix(~-1+zyg,data=d)
out1<-random.cif(c1,data=d,cause1=1,cause2=1,same.cens=TRUE,theta.des=mm)
summary(out1)
pc1 <- predict(c1,X=1,se=0)
plot(pc1)

dl <- d[!d$truncated,]
dl <- ipw2(dl,cluster="id",same.cens=TRUE,time="time",entrytime="entry",cause="cause",
           strata="strata",prec.factor=100)
cl <- timereg::comp.risk(Event(time,cause)~+1+
		cluster(id),
		data=dl,cause=1,model="fg",
		weights=dl$indi.weights,cens.weights=rep(1,nrow(dl)),
            times=times,max.clust=NULL,n.sim=0)
pcl <- predict(cl,X=1,se=0)
lines(pcl$time,pcl$P1,col=2)
mm=model.matrix(~-1+factor(zyg),data=dl)
out2<-random.cif(cl,data=dl,cause1=1,cause2=1,theta.des=mm,
                 weights=dl$weights,censoring.weights=rep(1,nrow(dl)))
summary(out2)

mets documentation built on May 29, 2024, 3:51 a.m.