Methods Workshop

2023 Methods Workshop

Structural Equation Modeling Methods for Longitudinal Data

This two-day short course is intended as both a theoretical and practical introduction to structural equation modeling (SEM) methods specifically in service of addressing developmental/longitudinal research questions. Building upon participants’ knowledge of the multiple regression / general linear models, we will work up through measured variable path models, confirmatory factor models, and latent variable path models (general SEM) both cross-sectionally and then longitudinally. From there we will proceed into mean structure models and latent growth curve models, mention variants such as change score models and structured residual models, and touch upon practical issues such as covariates, missing data, and sample size determination. Examples will draw from a variety of disciplines, including but not limited to education and psychology, and sample Mplus code will be provided (as well as parallel R/lavaan code as available).

June 5th and 6th – 9:00 a.m. to 5:00 p.m.
In-person in Pullman (room TBD) and available on Zoom for other campuses

Presented by the Learning Performance Research Center, Educational Psychology program, and Department of Psychology

Presenter: Dr. Gregory R. Hancock

Dr. Hancock is Professor and Distinguished Scholar-Teacher, long-time Director of the Measurement, Statistics, and Evaluation program in the Department of Human Development and Quantitative Methodology at the University of Maryland, College Park, and Director of the Center for Integrated Latent Variable Research (CILVR). He is also co-host of the popular quantitative methods podcast Quantitude. His research interests include structural equation modeling and latent growth models, power, reliability, and the use of latent variables in (quasi)experimental design. His research has appeared in such journals as Psychometrika, Multivariate Behavioral Research, Structural Equation Modeling: A Multidisciplinary Journal, Psychological Methods, British Journal of Mathematical and Statistical Psychology, Journal of Educational and Behavioral Statistics, Educational and Psychological Measurement, Review of Educational Research, and Communications in Statistics: Simulation and Computation. He also co-edited the volumes Structural Equation Modeling: A Second Course (2006; 2013), The Reviewer’s Guide to Quantitative Methods in the Social Sciences (2010; 2019), Advances in Latent Variable Mixture Models (2008), Advances in Longitudinal Methods in the Social and Behavioral Sciences (2012), and Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton (2019). He is past chair of the SEM special interest group of the American Educational Research Association (three terms), serves on the editorial board of a number of journals including Psychological Methods, Multivariate Behavioral Research, and Structural Equation Modeling: A Multidisciplinary Journal, and has taught over 200 methodological workshops in the United States, Canada, and abroad. He is a Fellow of the American Psychological Association, American Educational Research Association, Association for Psychological Science, Society of Multivariate Experimental Psychology, and also received the 2011 Jacob Cohen Award for Distinguished Contributions to Teaching and Mentoring by the American Psychological Association.  .

Cost

$40 Faculty (in-person)
$20 Students (in-person)
$20 All virtual attendees

Registration includes workshop, course packet, and refreshments (in-person)

  • 2022 – Tracy Sweet, University of Maryland – An Introduction to Machine Learning for the Social Sciences
  • 2021 – Tenko Raykov, Michigan State University –  Longitudinal Modeling and Missing Data Analysis
  • 2019 – Matthew McCrudden, Pennsylvania State University – Mixed Methods
  • 2018 – Gregory Hancock, University of Maryland – Latent Growth Curve Modeling
  • 2017 – Roy Levy, Arizona State University – Foundations of Bayesian Statistical Modeling
  • 2016 – Todd D. Little, Texas Tech University – Measurement, design, and analysis issues in longitudinal modeling with a particular focus on the longitudinal CFA model as the basis for both panel and latent growth curve modeling.
  • 2015 – Gregory Hancock, University of Maryland – Second Course in Structural Equation Modeling
  • 2014 – Bethany Bray, Pennsylvania State University – An Introduction to Latent Class and Latent Profile Analysis
  • 2013 – Gregory Hancock, University of Maryland – A First Course in Structural Equation Modeling