lipcancer_Y

<p>The observations about the observed number of lip cancer cases in each Scotland county between 1975 and 1980.</p>

datasets

A Bayesian model selection approach for generalized linear mixed models.
Currently, 'GLMMselect' can be used for Poisson GLMM and Bernoulli GLMM. 'GLMMselect' can select fixed effects and random effects simultaneously.
Covariance structures for the random effects are a product of a unknown scalar and a known semi-positive definite matrix.
'GLMMselect' can be widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics.
'GLMMselect' is based on Xu, Ferreira, Porter, and Franck (202X), Bayesian Model Selection Method for Generalized Linear Mixed Models, Biometrics, under review.

Shuangshuang Xu

GLMMselect

Bayesian Model Selection for Generalized Linear Mixed Models

Marco Ferreira

Erica Porter

Christopher Franck

lipcancer_Y function


<div class="section" id="lipcancer-y">
<h3><code>lipcancer_Y</code></h3><p></p><p>
</p><p>A vector with 56 observations.</p>
</div>


Format

The vector of observations for lip cancer case study — lipcancer_Y


<div class='section' id='lipcancer-y'>
<h3><code>lipcancer_Y</code></h3>


<p>A vector with 56 observations.</p>
</div>


lipcancer_Y: The vector of observations for lip cancer case study

Description

Usage

Arguments

Format

`lipcancer_Y`