数学与统计学院学术报告[2020] 112号

(高水平大学建设系列报告465号)

报告题目:  An Alternative to Post Hoc Model Modification in Confirmatory Factor Analysis: The Bayesian Lasso

报告人：潘俊豪（中山大学）

报告时间：2020年11月20日周五上午10:00-11:00　　　　　　　　　　　　 　　

报告地点：腾讯会议 会议号码：781692274　 　　　　　　　　　　　　

报告内容：As a commonly used tool for operationalizing measurement models, confirmatory factor analysis (CFA) requires strong assumptions that can lead to a poor fit of the model to real data. The post-hoc modification model approach attempts to improve CFA fit through the use of modification indexes for identifying significant correlated residual error terms. We analyzed a 28-item emotion measure collected for n = 175 participants. The post-hoc modification approach indicated that 90 item-pair errors were significantly correlated, which demonstrated the challenge in using a modification index, as the error terms must be individually modified as a sequence. Additionally, the post-hoc modification approach cannot guarantee a positive definite covariance matrix for the error terms. We propose a method that enables the entire inverse residual covariance matrix to be modeled as a sparse positive definite matrix that contains only a few off-diagonal elements bounded away from zero. This method circumvents the problem of having to handle correlated residual terms sequentially.  By assigning a Lasso prior to the inverse covariance matrix, this Bayesian method achieves model parsimony as well as an identifiable model. Both simulated and real data sets were analyzed to evaluate the validity, robustness, and practical usefulness of the proposed procedure.

报告人简历:  潘俊豪，中山大学心理学系副教授，2005年本科毕业于中山大学统计科学系统计学专业（本科第一专业）和中山大学计算机科学系计算机科学与技术专业（本科第二专业），2009年获得香港中文大学统计学博士学位（硕博连读），同年以“中山大学百人计划”人才引进进入心理学系任教，2014年入选广东省高等学校“千百十工程”第八批校级培养对象。2020年获得教育部第八届高等学校科学研究优秀成果奖（人文社会科学）——青年成果奖。完成并在研多项国家级科研项目（包括国家自然科学基金面上项目、青年项目、数学天元基金项目以及教育部人文社会科学研究规划基金项目）。至今发表学术论文超过30篇，合作翻译并出版了《结构方程模型: 贝叶斯方法》一书。担任British Journal of Mathematical and Statistical Psychology, Computational Statistics & Data Analysis, Multivariate Behavioral Research, Psychometrika, Statistics in Medicine, Structural Equation Modeling: A Multidisciplinary Journal, 心理学报, 心理科学, 心理科学进展等国内外著名学术期刊审稿专家。具体介绍请看http://psy.sysu.edu.cn/teacher/308.

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数学与统计学院

2020年11月19日