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Activity Number: 130
Type: Contributed
Date/Time: Monday, August 1, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #320911
Title: Novel Application of a Weighted Zero-Inflated Negative Binomial Model in Modeling Count Data from a Complex Survey
Author(s): Mulugeta Gebregziabher* and Lin Dai
Companies: Medical University of South Carolina and Medical University of South Carolina
Keywords: HIV ; multi-country survey data ; negative binomial ; regional variation ; zero-inflation

We demonstrate a novel application of a weighted zero-inflated negative binomial model to quantify regional variation in HIV-AIDS prevalence in sub-Saharan African countries. We use data from latest round of the Demographic and Health survey (DHS) conducted in three countries (Ethiopia-2011, Kenya-2009 and Rwanda-2010). The outcome is an aggregate count of HIV cases in each census enumeration area (CEA) from the DHS of the three sub-Saharan African countries. Data are characterized by excess zeros and heterogeneity due to clustering. We compare several scale-weighting approaches to account for the complex survey design and clustering in a zero inflated negative binomial (ZINB) model. Finally, we provide marginalized rate ratio (RR) estimates from the best ZINB model.

Authors who are presenting talks have a * after their name.

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