Distribution-free inference of zero-inflated binomial data for longitudinal studies |
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Authors: | H He W Wang R Gallop P Crits-Christoph Y Xia |
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Institution: | 1. Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA;2. Department of Mathematics and Applied Statistics, West Chester University, West Chester, PA 19383, USA;3. Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA |
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Abstract: | Count responses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated Poisson (ZIP) and zero-inflated negative binomial models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or ZIP distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling ZIB-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data. |
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Keywords: | bounded count response COMBINE Study distribution-free models generalizedestimating equations structural zero zero-inflated binomial |
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