[R] simulate binary data from a logistic regression model

[kjetil@entelnet.bo]

On 9 Oct 2003 at 11:38, Michele Grassi wrote:

Here is one way of doing it:

> x <- rnorm(1000)
> beta <- 1
> p <- 1/(1+exp(-beta*x))
> o <- order(x)
> plot( x[o], p[o], ylim=c(0,1), type="l")
> y <- rbinom(1000, 1, prob=p)
> model <- glm(y ~ x , family=binomial)
> summary(model)
.
.
.

> B <- 1000 # number of simulation replications
> coefs <- matrix(0, B, 2)
> for (i in 1:B) {
+    coefs[i, ] <- coef(glm(rbinom(1000,1,prob=p) ~ x, 
family=binomial))
+ }
> hist( coefs[,1])
> hist(coefs[,2])
> plot(coefs)



Kjetil Halvorsen

Hi.
How can i simulate a binary data set from a logistic 
regression model?I need to manipulate parameters and so 
obtain my set of data.
I want to show the improve in analyzing binary data 
with GLM(binomial) model instead of classical ANOVA or 
NON-MODELS procedures(relative risk-odds ratio-Pearson 
test of godness of fit...)
Can you say me what is the right function to use?
Do you know any interesting simulation in the web?

Thank you.
Michele.

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