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Activity Number: 183
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #317566 View Presentation
Title: Analysis of Bivariate Count Data That Occur in Health Care Studies
Author(s): N. Rao Chaganty* and Pooja Sengupta
Companies: Old Dominion University and Old Dominion University
Keywords: Count data ; Bivariate Poisson ; Inflated counts ; Mixture distribution ; Twin studies
Abstract:

Count data are common in health care studies and in many instances such as twin or cross over studies, the data consists of dependent bivariate counts. For instance, Carlin et al. (1987, Journal of Pediatrics) present bivariate data that consists of the number of infections in both ears of toddlers over a period of six months. A careful examination of the data shows that the frequencies of (0,0) and (2,2) cells are high. To analyze such data we introduce a bivariate doubly-inflated Poisson distribution (BDIP). We discuss the BDIP model distributional properties, parameter estimation and goodness of fit to the data.


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