# ipw: Inverse Probability of Censoring Weights In mets: Analysis of Multivariate Event Times

## Description

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

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```ipw( formula, data, cluster, same.cens = FALSE, obs.only = TRUE, weight.name = "w", trunc.prob = FALSE, weight.name2 = "wt", indi.weight = "pr", cens.model = "aalen", pairs = FALSE, theta.formula = ~1, ... ) ```

## Arguments

 `formula` Formula specifying the censoring model `data` data frame `cluster` clustering variable `same.cens` For clustered data, should same censoring be assumed (bivariate probability calculated as mininum of the marginal probabilities) `obs.only` Return data with uncensored observations only `weight.name` Name of weight variable in the new data.frame `trunc.prob` If TRUE truncation probabilities are also calculated and stored in 'weight.name2' (based on Clayton-Oakes gamma frailty model) `weight.name2` Name of truncation probabilities `indi.weight` Name of individual censoring weight in the new data.frame `cens.model` Censoring model (default Aalens additive model) `pairs` For paired data (e.g. twins) only the complete pairs are returned (With pairs=TRUE) `theta.formula` Model for the dependence parameter in the Clayton-Oakes model (truncation only) `...` Additional arguments to censoring model

Klaus K. Holst

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## Not run: data("prt",package="mets") prtw <- ipw(Surv(time,status==0)~country, data=prt[sample(nrow(prt),5000),], cluster="id",weight.name="w") plot(0,type="n",xlim=range(prtw\$time),ylim=c(0,1),xlab="Age",ylab="Probability") count <- 0 for (l in unique(prtw\$country)) { count <- count+1 prtw <- prtw[order(prtw\$time),] with(subset(prtw,country==l), lines(time,w,col=count,lwd=2)) } legend("topright",legend=unique(prtw\$country),col=1:4,pch=-1,lty=1) ## End(Not run) ```

### Example output ```Loading required package: timereg