报告时间：2019年1月16日 9:00-10:00
报告地点：明德主楼1016会议室
报告主题：Joint Mean and Covariance Modeling of Multiple Health Outcome Measures
报告摘要：
Health exams determine a patient’s health status by comparing the patient’s measurement with a population reference range, a 95% interval derived from a homogeneous reference population. Similarly, most of the established relation among health problems are assumed to hold for the entire population. We use data from the 2009 - 2010 National Health and Nutrition Examination Survey (NHANES) on four major health problems in the U.S. and apply a joint mean and covariance model to study how the reference ranges and associations of those health outcomes could vary among subpopulations. We discuss guidelines for model selection and evaluation, using standard criteria such as AIC in conjunction with posterior predictive checks. The results from the proposed model can help identify subpopulations in which more data need to be collected to refine the reference range and to study the specific associations among those health problems.
报告人简介:
牛晓月教授本科毕业于北京大学数学学院金融数学专业，在西雅图华盛顿大学获得统计学博士学位。之后加入宾夕法尼亚州立大学（PSU）统计系。科研方向主要包括social network models, small area estimation, Bayesian hierarchical models, statistical applications in global health, and statistical consulting.在PSU期间一直担任统计咨询中心管理主任，主要负责统计咨询中心与各个院系间的长期短期咨询合作项目。曾担任2018年北美统计协会(ASA)咨询组(Section of Statistical Consulting)的理事，负责组织2018年度的统计年会(JSM)与统计咨询相关的报告。
2018年秋季到2019年夏季牛教授在北京学术休假。在此期间，担任清华大学统计咨询中心副主任，主持咨询中心的各项业务。2018年秋季同时在北大数学学院给高年级本科生和研究生开设统计咨询课程，并与数学学院和统计中心合作建立北大的统计咨询中心。