#
Logit_normal GLMM R Package

## The R Package

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
vignette
or the R help file for the
`bnlogl`

and
`bnbigw`

functions.

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 It

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.

## Supporting Materials for the Paper

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.