New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes

TL;DR

This paper introduces new estimators for the intracluster correlation coefficient in clustered multinomial data, addressing the challenge of unequal cluster sizes where existing methods are limited.

Contribution

It proposes novel estimators specifically designed for overdispersion in clustered multinomial models with unequal cluster sizes.

Findings

New estimators improve accuracy in overdispersion measurement

Addresses gap in methods for unequal cluster sizes

Enhances statistical analysis of clustered multinomial data

Abstract

It is usual to rely on the quasi-likelihood methods for deriving statistical methods applied to clustered multinomial data with no underlying distribution. Even though extensive literature can be encountered for these kind of data sets, there are few investigations to deal with unequal cluster sizes. This paper aims to contribute to fill this gap by proposing new estimators for the intracluster correlation coefficient.