> I have run a logistic regression, used Gelman et al.'s car package
> to simulate the parameter estimates of that model, and have plotted
> the probability (using Gelman et al.'s invlogit() function) of the
> dependent variable being 1 given the value of a particular
> independent variable is at its mean. The plot has probabilities on
> the y-axis and the number (1-1000) of the simulation run on the x-axis.
>
> What I would like to do is to make the points that make up the 95%
> CI a different color from the points outside that CI. In other
> words, I would like the points from 1-24, and 976-1000 to be one
> color (the default color is fine), and the points 25-975 to be a
> different color. How would I do this?
>
> In case there is some confusion, here is example code, with only
onepredictor:
>
> set.seed(23)
> y<-rbinom(100,1,0.1)
> x<-rnorm(100)
> fit.1<-glm(y~x1, family=binomial(link="logit"))
> library(car)
> sim.fit.1<-sim(fit.1, 1000) #Simulate the parameter estimates of
> fit.1 1000 times
> plot(sort(invlogit(sim.fit.1$beta[,1]+sim.fit.2$beta[,2]*mean(x1))))
Running your code throws an error for me (can't find the 'sim' function -
is it in another library?). I think this is what you are trying to
achieve though
plot(1:20, col=c(rep("red",5), rep("blue",10), rep("red",5)))
Regards,
Richie.
Mathematical Sciences Unit
HSL
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