I forgot to mention, the Design package is deprecated (which suggest
your version of R is rather dated, current is 2.15). The rms package
replaces Design.
On Thu, May 10, 2012 at 10:23 PM, Joshua Wiley <jwiley.ps...@gmail.com> wrote:
> Hi Grace,
>
> I seem to have sent an empty draft before. Anyway, something like
> this might be an approach (untested):
>
> require(rms)
> set.seed(10)
> dat <- data.frame(
> age = rnorm(500, 40, 10),
> race = factor(sample.int(2,500,TRUE), labels = c("a", "b")))
> X <- model.matrix(~ age + race, data = dat)
> b <- c(-2, .1, 3)
> rates <- exp(X %*% b)
> # distribution of survival time
> dat$survtime <- 100 * rexp(500, rate = rates)
> # indicator for censored/observed
> dat$cens <- dat$survtime > 10
> # new survival time values with censored
> dat$survtime <- pmin(dat$survtime, 10)
> test <- survreg(Surv(survtime, cens) ~ age + race, data = dat)
> summary(test)
>
> Cheers,
>
> Josh
>
> On Thu, May 10, 2012 at 7:41 PM, Grace Ma <grace.yanfe...@gmail.com> wrote:
>> Hi,
>> I am trying to simulate a regression on survival data under a few
>> conditions:
>> 1. Under different error distributions
>> 2. Have the error term be dependent on the covariates
>>
>> But I'm not sure how to specify either conditions. I am using the Design
>> package to perform the survival analysis using the survreg, bj, coxph
>> functions. Any help is greatly appreciated.
>>
>> This is what I have so far:
>> survtime <- 10*rexp(500) #distribution of survival time
>> cens <- ifelse(survtime > 10, 0, 1) #indicator for censored/observed
>> survtime <- pmin(survtime, 10) #new survival time values with censored
>> info
>> age <- rnorm(200, 40, 10) #age variable
>> race <- factor(sample(c('a','b'),500,TRUE)) #categorical variable
>> test <- bj(Surv(survtime, cens) ~ rcs(age,5) + race)
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, Statistical Consulting Group
> University of California, Los Angeles
> https://joshuawiley.com/
--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
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