//SEM Foundations UCLA
SEM Foundations UCLA 2018-10-09T20:26:31+00:00

Structural Equation Modeling (SEM) Foundations

Comprehensive Structural Equation Modeling Statistics Seminar UCLA Campus

An comprehensive 3-day Stats Camp course on the Craft of SEM.

This camp is an advanced intensive short course using latent variable models also called structural equation models. The course will be a series of lectures and exercises to provide you with advanced training in the use of SEM for the analysis of both cross-sectional and longitudinal data. Even if you have taken a prior course on SEM, this comprehensive course will serve as a refresher on basic concepts but also introduce you to the latest advances in the craft of structural equation modeling. Participants from a variety of fields, including sociology, psychology, education, human development, marketing, business, biology, medicine, political science, and communication, will benefit from the course.

Participants will receive an electronic copy of all course materials, including lecture slides, practice datasets, software scripts, relevant supporting documentation, and recommended readings. Participants will also have access to a video recording of the course.

UCLA Camp: March 26 – 28, 2018
University of California, Los Angeles


FAQ

Topics include:

  • 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
  • Multilevel and multiple group SEM
  • Using Phantom Constructs
  • Multiple group modeling
Payment Options

$1,095 Faculty/Professional or $945 Student/Post-Doc

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Course Location:

UCLA Math Science Building – Room 5268
Parking Location – We Will E – mail Attendees With Parking Information

Travel Info:

Hotels are listed below in order of proximity to the UCLA Stats Camp course location:

http://luskinconferencecenter.ucla.edu
http://tivertonhouse.ucla.edu
Marriott Hotel

For those who may fly in, there is also a “Fly Away” bus that runs rom LAS to Westwood.

http://www.lawa.org/FlyAway/content.aspx?id=10167

Learning Objectives

This comprehensive 3-day statistics training institute on the craft of Structural Equation Modeling (SEM) will enable you to:

  • Learn both foundational concepts as well as critical new developments surrounding latent variable modeling –a comprehensive approach to learning the craft of SEM!
  • Understand the strengths and weaknesses of the different models that can be applied to both cross-sectional and longitudinal data.
  • Develop a clear understanding of how models can be specified and adapted to address your specific needs and questions.
  • Gain knowledge of the ways in which you should formulate models, test alternative models, and evaluate models with regard to statistical and practical significance.
  • Understand the mechanism of missing data and the optimal ways to treat missing data for both non-response and attrition
  • Learn how to create item parcels and employ them as optimal indicators for latent variable modeling.
  • Learn the distinction between mediation, moderation, and multiple additive effects as well as how to test for these effect in latent variable models

Syllabus

Monday March 26, 2018
8:30am Welcome and introductions
Foundations of SEM, including scaling, identification, and model evaluation
10:15-10:30 Snack and refreshment break
More Foundations of SEM including extensions such a using phantom constructs
12:00-1:00 Lunch break
Optimal Item Parceling!
2:30-2:45 Snack and refreshment break
Multiple Group Models and Testing for Factorial Invariance
4:30pm End
Tuesday March 27, 2018
8:30am Missing Data Mechanism and Modern Treatments
10:15-10:30 Snack and refreshment break
Mediation and How to Test It in SEM
12:00-1:00 Lunch break
Moderation and How to Test It in SEM
2:30-2:45 Snack and refreshment break
Catchup, Open Discussion, and consulting time
4:30pm End
Wednesday March 28, 2018
8:30am Longitudinal Panel Models
10:15-10:30 Snack and refreshment break
Various Longitudinal Models and Extensions
12:00-1:00 Lunch break
Latent Growth Curve Models
2:30-2:45 Snack and refreshment break
4:30pm End

Instructor: Todd D. Little Ph.D.

todd little phd statistics instructor

Todd D. Little, PhD is a Professor and director of the Institute for Measurement, Methodology, Analysis and Policy at Texas Tech University. He is widely recognized for his quantitative work on various aspects of applied SEM (e.g., modern missing data treatments, indicator selection, parceling, modeling developmental processes) as well as his substantive developmental research (e.g., action-control processes and motivation, coping, and self-regulation). His work has garnered over 24,500 citations with an h-index of 78 and an i10-index of 183. In 2001, he was elected to membership in the Society for Multivariate Experimental Psychology, and in 2009, he was elected President of APA’s Division 5 (Evaluation, Measurement, and Statistics). He is a fellow in APA, APS, and AAAS. In 2013, he received the Cohen award from Division 5 of APA for distinguished contributions to teaching and mentoring and in 2015 he received the inaugural distinguished contributions award for mentoring developmental scientists from the Society for Research in Child Development. Both awards cited his founding of Stats Camp (Statscamp.org) in 2003 and its ongoing impact on shaping the quality of scientific inquiry for both past and future generations of researchers.

Co-Instructor: Elizabeth Grandfield M.A.

SEM Foundations Course UCLAElizabeth is a doctoral student in Quantitative Psychology at the University of Kansas. Her research focuses on evaluating measurement invariance with an emphasis in longitudinal designs. In areas of applied research, Elizabeth has been involved in longitudinal children studies at Juniper Gardens as well as a national nursing study at Kansas University Medical Center, both in Kansas City. She also received the 2011 Multivariate Software Award, presented by Peter Bentler and Eric Wu. Elizabeth has been involved in Stats Camp since 2012.

Software and Computer Support

Participants need to bring a laptop computer with Wi-Fi capabilities. We strongly recommend that you also bring an extension cord or power strip

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.

The course will support LISREL, Mplus and laavan. Previous knowledge of LISREL, Mplus or laavan is preferred but not required.

Course Prerequisites

Required:

  • Proficiency in multiple linear regression.
  • At least limited experience with continuous latent variable models, e.g., exploratory and confirmatory factor analysis (EFA; CFA) and structural equation modeling (SEM).
  • 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 SEM.
  • Modern missing data treatments
  • Parceling procedures
  • Multiple group SEM
  • Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.

Course Files

Links to course files for those who enrolled in the course will be emailed 24 – 48hrs prior to course start date. Please download these files onto your computer on the first day of the course. The files are password protected to respect the intellectual property rights of the instructors. By using your login information, you agree not to share your login information or the content protected by it.

Course files and downloads will be emailed 24 – 48hrs prior to the first day of class.

Course Certificate

Upon completion of the course you may request an official Stats Camp print-ready PDF certificate.  Please contact us here to request a digital copy.

Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Course Resources