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]]
On Thu, May 10, 2012 at 7:41 PM, Grace Ma <grace.yanfei.m at 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]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > 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/
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.yanfei.m at 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]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> 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/