He H, Wang W J, Hu J, Gallop R, Crits-Christoph P, Xia Y L
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA.
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA ; College of Basic Science and Information Engineering, Yunnan Agricultural University, Kunming, Yunnan, China, 650201.
J Appl Stat. 2015 Oct 1;42(10):2203-2219. doi: 10.1080/02664763.2015.1023270. Epub 2015 Mar 18.
Count reponses 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 (ZINB) 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 zero-inflated Poisson (ZIP) distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling zero-inflated binomial (ZIB)-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.
在医学和社会心理研究中，尤其是在酒精和艾滋病研究中，含有结构性零值的计数响应非常常见，零膨胀泊松（ZIP）模型和零膨胀负二项式（ZINB）模型被广泛用于对此类结果进行建模。然而，由于诸如饮酒天数等饮酒结果是给定时间段内的计数，其分布在上方受到上限（该时间段的总天数）的限制，因此在存在结构性零值的情况下，它们本质上遵循二项式或零膨胀二项式（ZIB）分布，而不是泊松或零膨胀泊松（ZIP）分布。在本文中，我们开发了一种新的半参数方法，用于对横截面数据和纵向数据中类似零膨胀二项式（ZIB）的计数响应进行建模。我们用模拟研究数据和实际研究数据说明了这种方法。
