学术报告
报告题目：Semiparametric Zero-Inflated Modeling in Multi-Ethnic Study of Atherosclerosis (MESA)
报告人：刘海
生物统计系，Indiana University School of Medicine
时间：3月9日（周五）上午10:00-11:00
地点：理科一号楼1303
摘要：Zero-inflated data abound in health science and many other areas. In this talk, we analyze the Agatston score of coronary artery calcium (CAC) from the Multi-Ethnic Study of Atherosclerosis (MESA) using semiparametric zero-inflated modeling approach, where the observed CAC scores from this cohort consist of high frequency of zeroes and continuously distributed positive values. Both partially constrained and unconstrained models are considered to investigate the underlying biological processes of CAC development from zero to positive, and from small amount to large amount. A model selection procedure based on likelihood cross-validation is adopted to identify the optimal model, which is justified by comparative Monte Carlo studies. A shrinkaged version of cubic regression spline is used for model estimation and variable selection simultaneously. When applying the proposed methods to the MESA data analysis, we show that the two biological mechanisms influencing the initiation of CAC and the magnitude of CAC when it is positive are better characterized by an unconstrained zero-inflated normal model. The proposed highly flexible statistical framework can be applied to zero-inflated data analyses in other scientific fields.
This talk is based on joint work with Shuangge Ma, Richard Kronmal and Kung-Sik Chan.
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