This web page is about an R package (written by Yun Ju Sung and Charles J. Geyer) for doing Logit-Normal generalized linear mixed models (GLMM) using ordinary, independent and identically distributed Monte Carlo.
For more info see the package
or the R help file for the
New! The previous version did not install under R-3.0.0. The current version (link below) does.
The source code for the library is
A paper about the theory used by this package and using the package for examples
Monte Carlo Likelihood Inference for Missing Data Models
by Yun Ju Sung and Charles J. Geyer
has been submitted (5 Jan 2005) and revised and resubmitted (10 Jan 2006) and a preprint in PDF is available here.
Of no real interest except that the proofs are longer and more detailed is the first draft PDF.
Detailed verification of conditions of the theorems in the paper for the models done by the package.
A redo for the revision of the Booth and Hobert example in the paper.
A new example for the revision from Coull and Agresti.
A redo for the revision of the salamander example, also from Booth and Hobert, data originally from McCullagh and Nelder.