主 题：Challenges in Age-Period-Cohort Models and Applications to Economics, Marketing and Health Research
主讲人：Wenjiang Fu，University of Huston
主办单位：统计研究中心 统计学院 科研处
Wenjiang Fu，现为休斯敦大学数学系教授，MD安德森癌症中心生物统计学兼职教授。其主要研究方向是统计，生物医学等。曾主持研究基金项目10余项。现为Annals of Biometrics and Biostatistics的主编，PLoS ONE统计方向的审稿人；Open Access Medical Statistics，Journal of Nutritional Biochemistry和Journal of Sociological Research的编委。目前，Fu 教授出版专著2本，开设特刊2栏，在国际顶级期刊杂志发表论文56篇，会议论文发表17篇，做特邀报告86场，会议口头报告24场。
In economics, marketing research and business management, it is important to estimate the temporal trend of sales of products or the market share of a business during a period of time. In public health likewise, it is crucial to estimate the temporal trend of chronic disease (cancer, cardiovascular diseases, etc.) mortality rates. Often the sales of products vary with the age of consumers (e.g. sales of cosmetic products or life insurance policies), and the mortality rate varies with the age of patients (e.g. mortality rate of breast cancer), thus are reported by age group. More importantly, they also vary largely with the cohort (or generation) effect, which shows large difference between the older generations and younger generations. This presents a major challenge in statistical modeling - the identifiability problem in regression models with linearly dependent covariates, which has perplexed the statistical community for decades. I will present this complicated problem using simple graphical method, and present the most recent advances in addressing this identifiability problem. I will also demonstrate some novel methods with economics, public health and insurance policy purchase data.