mclogit 0.4 published on CRAN

A new version 0.4 of package mclogit has been published on CRAN, which adds a few new features to the previously published version.

One highlight of the new release is improved support for multinomial baseline logit models, i.e. models for categorical dependent variables with unordered categories (a.k.a. nominal-level dependent variables) with help of the function mblogit(). Such models could already be fitted with mclogit(), yet this required some additional work in data-management and model construction.

The new mblogit() function allows to fit models with categorical dependent variables right away. Its output will be numerically identical with the output of multinom from the package nnet, but the results are reported in more "conventional" way similar to to the results of glm() and the like.

At present, there is no support for random effects in multinomial baseline logit models. These are going to be added in the next release (0.5), along with random slopes in multinomial conditional logit models.