How to plot decision boundary in R for logistic regression model?

I made a logistic regression model using glm in R. I have two independent variables. How can I plot the decision boundary of my model in the scatter plot of the two variables. For example, how can I plot a figure like: http://onlinecourses.science.psu.edu/stat557/node/55

Thanks.

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set.seed(1234)

x1 <- rnorm(20, 1, 2)
x2 <- rnorm(20)

y <- sign(-1 - 2 * x1 + 4 * x2 )

y[ y == -1] <- 0

df <- cbind.data.frame( y, x1, x2)

mdl <- glm( y ~ . , data = df , family=binomial)

slope <- coef(mdl)[2]/(-coef(mdl)[3])
intercept <- coef(mdl)[1]/(-coef(mdl)[3])

library(lattice)
xyplot( x2 ~ x1 , data = df, groups = y,
panel=function(...){
panel.xyplot(...)
panel.abline(intercept , slope)
panel.grid(...)
})


I must remark that perfect separation occurs here, therefore the glm function gives you a warning. But that is not important here as the purpose is to illustrate how to draw the linear boundary and the observations colored according to their covariates.

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I hope I am not old fashioned if I use lattice :-) –  suncoolsu Jan 13 '11 at 2:47
I also hope that if this is a HW problem, you will not simply copy paste. –  suncoolsu Jan 13 '11 at 2:54
Thanks. This is not a HW question and the answer is helpful for me to understand my model. –  user2755 Jan 13 '11 at 4:25
oh yes you are :) –  mpiktas Jan 13 '11 at 8:09
Can someone explain me the logic behind the slope and intercept? (regarding the logistic model) –  Fernando Jan 9 at 12:29
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