# A Logit-Normal GLMM Dataset from Booth and Hobert

### Description

This data set contains simulated data from the paper of Booth and Hobert referenced below.

### Usage

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### Format

A data frame with 3 columns:

- y
Response vector.

- x1
Fixed effect model matrix. The matrix has just one column vector.

- z1
Random effect model matrix. The matrix has just one column vector.

### Details

This data set was generated by Booth and Hobert using a single variance component, a single fixed effect, no intercept, and a logit link.

### References

Booth, J. G. and Hobert, J. P. (1999). Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm. Journal of the Royal Statistical Society Series B (Statistical Methodology) 61, 265–285.

### Examples

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