时 间：下午3:30
地 点：北院卓远楼305会议室
主讲人：潘建新教授
Title: Case-deletion Diagnostics for Linear Mixed Models
Abstract:
Statistical diagnostics for linear mixed models is always challenging because of the complexity of the models when considering detection of outliers and identification of influential subjects/observations. Little work was done in the literature and lots of efforts have to be made for the research topics. Based on the Q-function, the conditional expectation of the logarithm of the joint-likelihood between responses and random effects, we propose a case-deletion approach to identify influential subjects and influential observations in linear mixed models. The models considered here are very broad in the sense that any covariance structures can be specified in the covariance matrices of the random effects and random errors. Analytically explicit forms of diagnostic measures for the fixed effects and variance components are provided. Comparisons with existing methods, including likelihood-based case-deletion and local influence methods, are made. Numerical results, including real data analysis and simulation studies, are presented for both illustration and comparison.
潘建新，英国曼彻斯特大学数学学院统计系教授，我校统计与数学学院特聘教授。于1996年在香港浸会大学获统计学博士学位。其研究方向包括纵向数据分析、生存数据分析、广义估计方程、生长曲线模型、均值与方差的同时建模，缺失数据问题及统计诊断。潘建新教授致力于统计方法的研究及其在生物、医学及金融领域内的应用研究。2002年在Springer出版社出版《生长曲线模型及统计诊断》专著（英文版；与方开泰教授合著）。目前担任Biometrics杂志编委（Associated Editor）。