R package for fixed-effect logistic regression I'm looking for an R package for estimating the coefficients of logit models with individual fixed-effect (individual intercept) using Chamberlain's 1980 estimator. It is often known as Chamberlain's fixed-effect logit estimator.  
It's a classic estimator when dealing with binary outcome panel data (at least in econometrics), but I just don't find anything related to it in the CRAN.
Any clue?
 A: You can run the Chamberlains model using glmer. It is basically a RE model but with more variables:
glmer(y~X + Z + (1|subject), data, model=binomial("probit"))



*

*X are the variables you consider explain your fixed effect model (a simple case it is the mean of Z)

*Z are your exogenous variables

*Subject is the variable where the heterogeneity comes from


I hope this helps.
A: Conditional logistic regression (I assume that this is what you refered to when talking about Chamberlain's estimator) is available through clogit() in the survival package. I also found this page which contains R code to estimate conditional logit parameters. The survey package also includes a lot of wrapper function for GLM and Survival model in the case of complex sampling, but I didn't look at.
Try also to look at logit.mixed in the Zelig package, or directly use the lme4 package which provide methods for mixed-effects models with binomial link (see lmer or glmer).
Did you take a look at Econometrics in R, from Grant V. Farnsworth? It seems to provide a gentle overview of applied econometrics in R (with which I am not familiar).
A: The mclogit package seems to implement conditional logit of the Chamberlain variant.
