Specification and estimation of conditional logit models of binary responses and multinomial counts is provided, with or without alternative- specific random effects. The current implementation of the estimator for random effects variances uses a Laplace approximation (or PQL) approach and thus should be used only if groups sizes are large.
2014-10-13: Simplified some namespace dependencies. Eliminated useless pseudo-R-squared statistics form getSummary.mclogit
2014-08-23: Added 'anova' methods
2014-03-10: Refactored code -- algorithms should be more transparent and robust now (hopefully!). mclogit without and with random effects can handle missing values now. Fixed predict method -- use of napredict; handles single indep-variable situation now. Fixed embarassing typo -- prior weights do work now (again?). Included AIC and BIC methods contributed by Nic Elliot [email protected]