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$ 1,395.00

IN PERSON – 5-day Statistics Short Course

Longitudinal Structural Equation Modeling (LSEM) Seminar Overview:

Do you have repeated measurements? Have you collected data over multiple timepoints? Do you need help designing your longitudinal study? If so, this is your course! Let us help you appropriately design your longitudinal study and analyze your data in the SEM latent variable framework using Longitudinal Structural Equation Modeling (LSEM). This framework will allow you more flexibility in evaluating your research questions over time as well as test assumptions that traditional techniques like ANOVA ignore.

Seminar Topics:

  • Design and measurement issues in cross-sectional and longitudinal research
  • Traditional panel designs
  • Overview of missing data
  • Latent growth curve modeling
  • Testing for Mediation and Moderation
  • Using Phantom Constructs
  • Longitudinal Measurement Invariance – Multiple Group LSEM
  • Growth Mixture Models

Seminar Description:

The seminar will be a series of lectures and computer workshops to provide participants with advanced training in the use of SEM for the analysis of longitudinal data.

Instructor: Todd D. Little, Ph.D.

Longitudinal SEM Training

Todd D. Little, Ph.D. is a Professor of Educational Psychology at Texas Tech University (TTU). Little is internationally recognized for his quantitative work on various aspects of applied SEM (e.g., indicator selection, parceling, modeling developmental processes) as well as his substantive developmental research (e.g., action-control processes and motivation, coping, and self-regulation). Prior to joining TTU, Little has guided quantitative training and provided consultation to students, staff, and faculty at the Max Planck Institute for Human Development’s Center for Lifespan Studies (1991-1998), Yale University’s Department of Psychology (1998-2002), and researchers at KU (2002-2013, including as director of the RDA unit at the Lifespan Institute and as director of the Center for Research Methods and Data Analysis). In 2001, Little was elected to membership in the Society for Multivariate Experimental Psychology, a restricted-membership society of quantitative specialists in the behavioral and social sciences.

In 2009, he was elected President of APA’s Division 5 (Evaluation, Measurement, and Statistics). He founded, organizes, and teaches in the internationally renowned ‘Stats Camps’ each June (see statscamp.org for details of the summer training programs) and has given over 150 workshops and talks on methodology topics around the world. As an interdisciplinary-oriented collaborator, Little has published with over 280 persons from around the world in over 65 different peer-reviewed journals. His work has garnered over 11,000 citations. He published Longitudinal Structural Equation Modeling in 2013 and he has edited five books related to methodology, including the Oxford Handbook of Quantitative Methods and the Guildford Handbook of Developmental Research Methods (with Brett Laursen and Noel Card). Little has served on numerous grant review panels for federal agencies such as NSF, NIH, and IES, and private foundations such as the Jacobs Foundation. He has been the principal investigator or co-principal investigator on over 15 grants and contracts and he has served as a statistical consultant on over 70 grants and contracts. In the conduct of his collaborative research, he has participated in the development of over 12 different measurement tools, including the CAMI, the Multi-CAM, the BALES, the BISC, the I FEEL, and the form/function decomposition of aggression.

Instructor: Whitney Moore, Ph.D.

Longitudinal SEM Course

Dr. Whitney Moore is an Assistant Professor of Kinesiology at East Carolina University. Whitney received her Ph.D. in the Psychosocial Aspects of Health and Physical Activity from the University of Kansas. She has been a Stats Camp instructor since 2012 (after experience being a “counselor” for SEM, Longitudinal SEM, and MLM). Whitney has taught graduate courses in research design, introduction to statistics, ANOVA, SEM, and measurement development at two different R1 institutions. Her research is at the intersection of advanced quantitative methods and psychosocial aspects applied to sport, exercise, and physical education contexts. This is particularly illustrated in her work on measurement development; helping to develop or modify 12 measures in the last 10 years. Whitney is particularly interested in planned missing data designs, finite mixture modeling, plus mediation and moderation in SEM.

Instructor: Zachary Stickley, Ph.D.

Longitudinal Structural Equation Modeling

Zachary, Ph.D. is a senior research scientist at Yhat Enterprises LLC. where he pursues his research interests in measurement design, applied latent variable modeling, and modern approaches to missing data. Dr. Stickley has also served as an instructor and coordinator for the Stats Camp Foundation since first joining the team as a graduate student in 2018. He received his Ph.D. in Educational Psychology from College of Education at Texas Tech University with a focus on research methodology, measurement design, and statistical modeling. He received his Master of Education degree from Texas Tech University and his Bachelor of Science in Psychology from Tarleton State University.

APA Continuing Education Credits:

Longitudinal Structural Equation Modeling (LSEM)

This course offers 26 hours of Continuing Education Credits. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

Learning Objectives:

The five-day training institute on Longitudinal Structural Equation Modeling (LSEM) will enable participants to:

  • Address design and measurement issues in longitudinal modeling.
  • Acquire understanding of the SEM concepts that are foundational to longitudinal SEM design.
  • Analyze longitudinal panel models in both a single group and multi-group configuration in CFA and SEM framework.
  • Incorporate mediation and moderation in a longitudinal framework.
  • Construct item parcels in a longitudinal framework.
  • Evaluate latent growth curve models.
  • Apply latent growth curve models in a multivariate and multiple group context.
  • Evaluate finite mixture models.
  • Interpret and evaluate covariance pattern mixture models.
  • Evaluate Growth mixture models.
  • Address missing data using FIML and MI methods.
  • Use modern missing data treatments to implement a planned missing data design.

Seminar Prerequisites:


  • Proficiency in multiple linear regression.
  • At least limited experience (e.g., graduate-level course) with continuous latent variable models, e.g., exploratory and confirmatory factor analysis (EFA; CFA) and structural equation modeling (SEM).
  • We strongly recommend that you attend our foundations of SEM as a pre-requisite to taking this advanced course. If you have not taken the foundations course, you should have extensive experience or have taken a graduate-level course on SEM before enrolling.
  • Intermediate proficiency with at least one statistical software package (e.g., SPSS, Stata, SAS, R, LISREL, Mplus, etc.).

Not required but advantageous:

  • At least limited experience (e.g., graduate-level course) with multivariate data analysis.

No level of proficiency beyond basic awareness is assumed for skills related to:

  • Longitudinal Structural Equation Modeling (LSEM).
  • Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.

Software and Computer Support:

Participants need a laptop computer with Wi-Fi and webcam capabilities.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Seminar Audience:

If you already have a strong background in the application of SEM to analyze the covariance structure of multivariate data and you need to learn how to apply more advanced models to longitudinal data, this seminar is for you. We strongly recommend that you attend our five-day intensive summer institute on the foundations of SEM as a pre-requisite to taking this five-day advanced seminar. If you have not taken the foundations Seminar, you should have extensive experience or have taken a graduate-level seminar on SEM before enrolling.

Participants from a variety of fields, including sociology, psychology, education, human development, marketing, business, biology, medicine, political science, and communication, will benefit from the seminar.

The seminar will support LISREL, Mplus or Laavan. Some assistance will be available for questions related to other structural modeling packages. Previous knowledge of LISREL, Mplus or Laavan is preferred but not required.

Seminar Files

Instructor will provide password on first day of seminar.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Summer Stats Camp 2024: Longitudinal Structural Equation Modeling (LSEM)
Monday June 10, 2024
9:00-10:45 Welcome and Introductions. Overview of Longitudinal Models
10:45-11:00 Rest Break
11:00-12:30 Design and Measurement Issues in Longitudinal Modeling
12:30-1:30 Rest Break
1:30-3:15 Review of Foundations of SEM
3:15-3:30 Rest Break
3:30-5:00 Longitudinal Panel Models: Basics
Tuesday June 11, 2024
9:00-10:45 Multiple-group Longitudinal Panel Models; CFA and SEM
10:45-11:00 Rest Break
11:00-12:30 Parcels and Parceling
12:30-1:30 Rest Break
1:30-3:15 Longitudinal Mediation & Moderation
3:15-3:30 Rest Break
3:30-5:00 Consultation
Wednesday June 12, 2024
9:00-10:45 Latent Growth Curve Modeling: Basics
10:45-11:00 Rest Break
11:00-12:30 Latent Growth Curve Modeling: Multivariate and Multiple Groups
12:30-1:30 Rest Break
1:30-3:15 Introduction to Finite Mixture Modeling
3:15-3:30 Rest Break
3:30-5:00 Introduction to growth mixture modeling / Consultation
Thursday June 13, 2024
9:00-10:45 Latent class growth analysis (LCGA)
10:45-11:00 Rest Break
11:00-12:30 Covariance Pattern Mixture Models
12:30-1:30 Rest Break
1:30-3:15 Growth mixture modeling (GMM)
3:15-3:30 Rest Break
3:30-5:00 Growth mixture modeling (GMM)
Friday June 14, 2024
9:00-10:45 Missing Data: Planned and Unplanned
10:45-11:00 Rest Break
11:00-12:30 Wrap-up then Individual Consultations
12:30-1:30 Rest Break
1:30-~3:30 Individual Consultations

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