Dear Sigalit,
On Nov 12, 2007 2:18 PM, sigalit mangut-leiba <[EMAIL PROTECTED]> wrote:
> Hello,
> I have a simple (?) simulation problem.
> I'm doing a simulation with logistic model and I want to reapet it 600
> times.
> The simulation looks like this:
>
> z <- 0
> x <- 0
> y <- 0
> aps <- 0
> tiss <- 0
> for (i in 1:500){
> z[i] <- rbinom(1, 1, .6)
> x[i] <- rbinom(1, 1, .95)
> y[i] <- z[i]*x[i]
> if (y[i]==1) aps[i] <- rnorm(1,mean=13.4, sd=7.09) else aps[i] <-
> rnorm(1,mean=12.67, sd=6.82)
> if (y[i]==1) tiss[i] <- rnorm(1,mean=20.731,sd=9.751) else tiss[i] <-
> rnorm(1,mean=18.531,sd=9.499)
> }
> v <- data.frame(y, aps, tiss)
> log_v <- glm(y~., family=binomial, data=v)
> summary(log_v)
>
> I want to do a repetition of this 600 times (I want to have 600 logistic
> models), and see all the coefficients of the covariates aps & tiss.
> Thanks in advance,
> Sigalit.
>
I won't comment on your general approach to simulation but does this
answer your question?
### Create an empty matrix to hold the results as they
### are created
Results <- matrix(NA, ncol = 3, nrow = 600)
for(i in 1:600) {
generate your data
Results[i, ] <- coef(glm(y~., family=binomial, data=v))
}
summary(Results)
Stephen
--
Rochester, Minn. USA
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