题目：广义潜变量模型在心理学研究中的应用

报告人：王月燕

报告人简介：Yueyan Wang, PhD, is a statistician at the UCLA Center for Health Policy Research. She provides statistical support to Center research projects and California Health Interview Survey (CHIS). Her major responsibilities include statistical modeling, small area estimation, GIS analysis, and statistical programming. She also serves as the scientific coordinator of * Ask*CHIS Neighborhood Edition (NE), a new public health dissemination tool for CHIS. She is responsible for coordinating the development and implementation of statistical methodology and programs, as well as production and quality control of small area estimates for *Ask*CHIS NE. Wang has served as statistical consultant and data analyst for a variety of research projects at the Center. She has expertise in applying multilevel models to clustered or longitudinal data, survey data analysis, psychometrics, small area estimation, and GIS analysis. Prior to joining the Center, she has provided statistical consultation to research projects in psychology and education at UCLA as a graduate student researcher. Wang received her PhD and MA in quantitative psychology from UCLA and her BS in psychology from Peking University in China.

时间：2013年12月13日 星期五 12:30-

地点： 哲学楼103会议室

邀请人：谢晓非

摘要：Generalized latent variable modeling unifies the principles behind latent variable modeling, which includes multilevel models, item response models, and structural equation models. This powerful integrated approach provided new tools for answering unique types of research questions. This talk will illustrate different applications of this integrated approach in psychological research, including Multilevel IRT, Growth Mixture Model, and Multilevel SEM.