2023 ISDSA Meeting

Workshop 5: From Latent Class Model to Latent Transition Model Using Mplus (In Chinese)

Time: 8am-11am, July 7, China Time / 8pm-11pm, July 6, US Eastern Time
Location： Virtual on Zoom (Free Registration)

Latent class modeling (LCM), a branch of latent variable modeling, has become increasingly popular among social researchers in recent years because of its superior capability for detecting unobserved heterogeneity in data. Unlike the traditional latent variable models that focus on extracting factors, the latent variable in a LCM is discrete and categorical，and its groups, called latent classes, provide a classification structure or statistical taxonomy for recovering the sub-population behind the sample. This workshop will briefly introduce the methodological concepts of LCM and pay more attention to the analytic techniques, using Mplus, for implementing latent class analysis as well as latent profile analysis along with a major extension for longitudinal data analysis, entitled latent transition analysis (LTA), which is used to examine how individuals transition in the latent class membership over time.

潜在类别模式作为潜在变数模型的一个分支，近年来广泛被社会科学研究者重视，主要是因为LCM在估计资料背后的潜在异质性的优越能力。有别于传统潜在变数模型专注于因素的萃取，LCM所估计得到的潜在变数是离散的类别，称为潜在类别，可以作为观察资料背后的次母体统计分类系统。本工作坊将简要介绍LCM的原理与方法学概念，但着重于实际以Mplus来进行潜在类别分析、潜在剖面分析，以及在纵贯资料分析上的应用，也就是潜在移转分析，借以检验个体的潜在类别属性如何随着时间而变动。

Hawjeng Chiou -- National Taiwan Normal University

Dr. Choiu is a distinguished professor of the College of Management at National Taiwan Normal University. His major interest is in applied psychometrics, particularly for the applications of advanced modeling techniques, such as Structural Equation Modeling, Multilevel Linear Modeling, and Latent Class Modeling, with substantial areas such as Human Resource Management, Organizational Behavior, and Psychological Testing as well as Creativity research. He has published multiple books on a variety of topics.

All Workshops

(1) Introduction to Social Network Analysis by Prof. Haiyan Liu from UC-Merced
(2) Longitudinal Data Analysis by Prof. Hongyun Liu from Beijing Normal University
(3) Practical Mediation Analysis by Prof. Laura Lu from University of Georgia and Prof. Qian Zhang from Florida State University
(4) Deep Learning Using R by Prof. Johnny Zhang from University of Notre Dame
(5) From Latent Class Model to Latent Transition Model Using Mplus by Prof. Hawjeng Chiou from National Taiwan Normal University
(6) Bayesian Longitudinal Data Modeling by Prof. Cynthia Tong from University of Virginia