I have searched the r-help archive and saw only one unanswered post related
to mine.
My design is as follows.
- y is Bernoulli response
- x1 is continuous variable
- x2 is categorical (factor) variable with two levels
The experiment is completely within subjects. That is, each subject
receives each combination of x1 and x2.
This is a repeated measures logistic regression set-up. The experiment will
give two ogives for p(y==1) vs x1, one for level1 and one for level2 of x2.
The effect of x2 should be that for level2 compared to level1, the ogive
should have a shallower slope and increased intercept.
I am struggling with finding the model using lme4. Here is a guess at it:
glmer(y~x1*x2 +(1|subject),family=binomial)
So far as I understand it, the 1|subject part says that subject is a random
effect. But I do not really understand the notation or how to specify that x
1 and x2 are repeated measures variables. In the end I want a model that
includes a random effect for subjects, and gives estimated slopes and
intercepts for level1 and level2.
Thanks very much for any help.
Stan
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