I might try something like:
data[data$flag1 == 1, "flag2"] <- runif(sum(data$flag1 == 1)) < 0.95
and similarly for the other case.
Hope this helps,
Michael
On Mon, Jun 18, 2012 at 12:29 PM, nqf <n.j.frank...@pgr.reading.ac.uk> wrote:
> Dear R-help,
>
> I am trying to write a function to simulate datasets of size n which contain
> two time-to-event outcome variables with associated 'Event'/'Censored'
> indicator variables (flag1 and flag2 respectively). One of these indicator
> variables needs to be dependent on the other, so I am creating the first and
> trying to use this to create the second using an if/else statement.
>
> My data structure needs to follow this algorithm (for each row of the data):
> If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
> Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
> otherwise
>
> I can set up this example quite simply using if else statements, but this is
> incredibly inefficient when running thousands of datasets:
> data<-as.data.frame(rbinom(10,1,0.5))
> colnames(data)<-'flag1'
> for (i in 1:n) {
> if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
> {data$flag2[i]<-rbinom(1,1,0.5)}
> }
>
>
> I think to speed up the simulations I would be better changing to
> vectorisation and using something like:
> ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5))
> but the rbinom statements here generate one value and repeat this draw for
> every element of flag2 that matches the 'if' statement on flag1.
>
> Is there a way to assign flag2 to a new bernoulli draw for each subject in
> the data frame with flag1=1?
>
> I hope my question is clear, and thank you in advance for your help.
>
> Thanks,
> Natalie
> PhD student, Reading University
>
> P.S. I am using R 2.12.1 on Windows 7.
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Trying-to-speed-up-an-if-else-statement-in-simulations-tp4633725.html
> Sent from the R help mailing list archive at Nabble.com.
>
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