Analyzing dependence in incidence of diabetes and heart problem using generalized bivariate geometric models with covariates

TitleAnalyzing dependence in incidence of diabetes and heart problem using generalized bivariate geometric models with covariates
Publication TypeJournal Article
Year of Publication2017
AuthorsIslam, MA, Chowdhury, RI, Sultan, KS
JournalJournal of Applied Statistics
Volume44
Issue16
Pagination2890-2907
Date PublishedFeb-12-2017
ISSN Number0266-4763
KeywordsDiabetes, Heart disease
Abstract

For analyzing incidence data on diabetes and health problems, the bivariate geometric probability distribution is a natural choice but remained unexplored largely due to lack of models linking covariates with the probabilities of bivariate incidence of correlated outcomes. In this paper, bivariate geometric models are proposed for two correlated incidence outcomes. The extended generalized linear models are developed to take into account covariate dependence of the bivariate probabilities of correlated incidence outcomes for diabetes and heart diseases for the elderly population. The estimation and test procedures are illustrated using the Health and Retirement Study data. Two models are shown in this paper, one based on conditional-marginal approach and the other one based on the joint probability distribution with an association parameter. The joint model with association parameter appears to be a very good choice for analyzing the covariate dependence of the joint incidence of diabetes and heart diseases. Bootstrapping is performed to measure the accuracy of estimates and the results indicate very small bias. © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

URLhttps://www.tandfonline.com/doi/full/10.1080/02664763.2016.1266467
DOI10.1080/02664763.2016.1266467
Short TitleJournal of Applied Statistics
Citation Key9059