July 4–6, 2023 | Shanghai, China

2023 ISDSA Meeting

Theme: Applied Data Science

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.


  • Hawjeng Chiou

    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

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The meeting is jointly supported by the International Society for Data Science and Analytics, the Society of Multivariate Experimental Psychology, the Fudan Institute for Advanced Study in Social Sciences, the College of Management of National Taiwan Normal University, and the Nanjing University of Posts and Telecommunications.

Sponsoring Journals
Selected papers will be published in the following journals: Fudan Journal of the Humanities and Social Sciences, Chinese Political Science Review, and Journal of Behavioral Data Science.


  • Hawjeng Chiou
    Distinguished Professor
    National Taiwan Normal University

  • Karl Ho
    Associate Professor
    University of Texas at Dallas

  • Hongyun Liu
    Beijing Normal University

  • Wen Qu
    Research Fellow
    Fudan University

  • Jiashan Tang
    Nanjing University of Posts and Telecommunications

  • Ke-Hai Yuan
    University of Notre Dame

  • Zhiyong Zhang
    University of Notre Dame

  • Contact information

    Telephone: 1-574-400-5868
    Email: meeting@isdsa.org
    Mail: P.O.Box 1471, ISDSA, Granger, IN 46530