On Sep 17, 2012, at 11:32 AM, john james wrote:
> Dear R users,
>
> I have the following problems. My dataset (dat) is as follows:
>
> a <- c(1,2,3)
> id <- rep(a, c(3,2,3))
> stat <- c(1,1,0,1,0,1,1,1)
> g <- c(0,0,0,0,0,0,1,0)
> stop <- c(1,2,4,2,4,1,1.5,3)
> dat <- data.frame(id,stat,g,stop)
>
> I want to creat a new dataset (dat2) with missing values
> such that when either g = =1 or stat = =0, the remaining rows for an
> individual subject is set to NA by using a new variable d (that states
> the exact time this
> happened from the stop variable). By this I mean dat2 that looks like,
>
> id <- rep(a, c(3,2,3))
> sta2<- c(1,1,NA,1,NA,1,NA,NA)
> g2<- c(0,0,NA,0,NA,0,NA,NA)
> stop2 <- c(1,2,NA,2,NA,1,NA,NA)
> d <- c(4,4,NA,4,NA,1.5,NA,NA)
>
> dat2 <- data.frame(id=id, stat2=sta2, g2=g2,stop2=stop2,d=d).
> suppressidx <- ave(dat$stat==0 | dat$g==1, dat$id, FUN=cumsum)
> suppress <- function(col) { ifelse( suppressidx, NA, col)}
> cbind(dat[1], sapply( dat[-1], function(x) suppress(x) ) )
id stat g stop
1 1 1 0 1
2 1 1 0 2
3 1 NA NA NA
4 2 1 0 2
5 2 NA NA NA
6 3 1 0 1
7 3 NA NA NA
8 3 NA NA NA
--
David Winsemius, MD
Alameda, CA, USA
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