LSEM-2022

Introduction to Longitudinal Structural Equation and Latent Growth Modeling

The Center for Integrated Latent Variable Research (CILVR)

presents the ONLINE short course

LONGITUDINAL STRUCTURAL EQUATION AND LATENT GROWTH MODELING

January 19-21, 2022 (Wednesday-Friday)

taught by

Gregory R. Hancock, University of Maryland

 

SHORT COURSE DESCRIPTION / TOPICS

This three-day short course is intended as both a theoretical and practical introduction to structural equation modeling approaches to longitudinal data analysis, building upon participants' prior exposure to basic principles of structural equation (covariance structure) modeling. Examples used in this short course draw from a variety of disciplines, including but not limited to the fields of education and psychology, and example code and output from the Mplus software package will be provided, as well as parallel R (lavaan) code.

TOPICS

  • mean structure models
  • cross-lagged panel models, structured residual models
  • linear and nonlinear latent growth models
  • time-independent and time-dependent covariates
  • missing data
  • latent change score models
  • growth mixture models
  • power / sample size determination
  • other topics as time allows

TARGET AUDIENCE

Graduate students, emerging researchers, continuing researchers

REQUISITE KNOWLEDGE

Participants should have had prior training that includes an introductory structural equation modeling course or workshop (although a brief review will be provided to start). No prior experience with longitudinal/growth models is assumed. Prior experience with the Mplus software is not required.

SOFTWARE

Models and hands-on exercises for this workshop will be done using the Mplus software. Participants are welcome to have the package loaded on their own computer, although this is not required. Parallel R (lavaan) code will also be made available.

DATES AND TIMES

January 19-21, 2022 (Wednesday-Friday)

10:00am-5:00pm Eastern Standard Time (UTC-5)

Instructor will determine timing of brief lunch break, as well as any other breaks.

REGISTRATION RATES

Professional: $495

Full-time student*: $295

*Full-time students must submit student status proof at https://go.umd.edu/CILVR-STUDENT for prompt processing of the registration.

Free for registered HDQM Department faculty and degree-seeking students, although you must register through the internal link. 

HOW TO REGISTER

One-time Registration:

- For professional and full-time student participants, please register using this link: https://go.umd.edu/LSEM-2022

- Full-time students must also submit the student status proof at https://go.umd.edu/CILVR-STUDENT for prompt processing of the registration. Note that it may take 2-3 business days for your registration to be processed.

Bundle Registration:

- Participants who wish to register for multiple CILVR short courses in 2021-2022 as a bundle and obtain ONE receipt for the bundle registrations could submit the request at https://go.umd.edu/CILVR-BUNDLE

HDQM Registration:

- HDQM department registrants can register using the following registration form: https://go.umd.edu/LSEM-2022-HDQM  

LOCATION AND PLATFORM

This workshop will be delivered entirely online via the video conferencing software Zoom (https://zoom.us/). 

Within a limited time, the video recordings of the short course will become available for both synchronous and asynchronous participants on Vimeo (https://vimeo.com/). The videos will be available for six months from the first date of the short course.

IMPORTANT COURSE DETAILS

Format: Participants will receive a personalized login code to use on their own computer to access a reliable live-stream of the short course over Zoom, showing the instructor as well as the handouts.

Materials: Participants will receive electronic copies of the short course materials, as well as any other relevant materials or information.

Timing/access: Participants may choose to watch the stream synchronously, or may elect to watch a recording of the short course asynchronously, or both. Recordings will be available to participants for six months from the start of the short course. This is especially useful for on-line participants in different time zones who may choose to watch at some later time than (but within six months of) the actual short course time. (Asynchronous participation does not include real-time chat with other on-line participants, although a visual record of prior chats will be viewable).

Technical support: Participants are responsible for installing the conferencing software Zoom on their own electronic devices and for obtaining a Zoom account that allows the participant to join Zoom meetings and webinars hosted by external organizations. Participants are assumed to be able to secure a reliable computer, internet browser, and Wi-Fi connection. Challenges at the user end must be resolved by the user. Fortunately, because the short course is recorded, users experiencing technical challenges can still “catch up” by watching the recordings to which they have access.

Content support: During the lecture, real-time content support for on-line participants is provided through real-time chat with the on-line (Zoom) participant community, with course facilitators, and with any quantitative methodology doctoral students also participating. 

REFUND POLICY

Full refund if cancellation occurs at least 10 business days prior to the workshop date; 50% refund if within 10 days of the first day of the course.

QUESTIONS?

For any questions, please contact Ms. Yi Feng: sem.cilvr@gmail.com  

ABOUT THE INSTRUCTOR

Gregory R. Hancock is Professor, Distinguished Scholar-Teacher, former 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 PsychometrikaMultivariate Behavioral ResearchStructural Equation Modeling: A Multidisciplinary JournalPsychological MethodsBritish Journal of Mathematical and Statistical PsychologyJournal of Educational and Behavioral StatisticsEducational and Psychological MeasurementReview 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 MethodsMultivariate 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. Dr. Hancock holds a Ph.D. from the University of Washington. He may be reached at ghancock@umd.edu.