A multivariate zero-inflated binomial model for the analysis of correlated proportional data

© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Détails bibliographiques
Publié dans:Journal of applied statistics. - 1991. - 49(2022), 11 vom: 22., Seite 2740-2766
Auteur principal: Deng, Dianliang (Auteur)
Autres auteurs: Sun, Yiguang, Tian, Guo-Liang
Format: Article en ligne
Langue:English
Publié: 2022
Accès à la collection:Journal of applied statistics
Sujets:Journal Article Correlated proportional data EM algorithm likelihood ratio test multivariate zero-inflated binomial score test stochastic representation
Description
Résumé:© 2021 Informa UK Limited, trading as Taylor & Francis Group.
In this paper, a new multivariate zero-inflated binomial (MZIB) distribution is proposed to analyse the correlated proportional data with excessive zeros. The distributional properties of purposed model are studied. The Fisher scoring algorithm and EM algorithm are given for the computation of estimates of parameters in the proposed MZIB model with/without covariates. The score tests and the likelihood ratio tests are derived for assessing both the zero-inflation and the equality of multiple binomial probabilities in correlated proportional data. A limited simulation study is performed to evaluate the performance of derived EM algorithms for the estimation of parameters in the model with/without covariates and to compare the nominal levels and powers of both score tests and likelihood ratio tests. The whitefly data is used to illustrate the proposed methodologies
Description:Date Revised 02.08.2022
published: Electronic-eCollection
Citation Status PubMed-not-MEDLINE
ISSN:0266-4763
DOI:10.1080/02664763.2021.1918649