Latent Growth Curve Modeling

A 2-Day Seminar Taught by Gregory Hancock, Ph.D.  

Read reviews of other seminars taught by Gregory Hancock 


Longitudinal data are ubiquitous throughout the social and behavioral sciences and beyond, where researchers have questions about the nature of change over time as well as its determinants. This two-day seminar provides a thorough introduction to latent growth curve models, which facilitate an assessment of longitudinal change from within the structural equation modeling (SEM) framework. 

The seminar will start with a quick review of SEM with measured and latent variables, illustrating the use of Mplus for such models. Next, latent means models, which add a mean structure to typical covariance-based structural models, will be introduced and illustrated with Mplus. The seminar will then review more traditional longitudinal models within an SEM framework (repeated measure models, panel models, etc.) to finish laying the necessary foundations.

The seminar will then move into a thorough coverage of traditional linear latent growth models, including but not limited to different time centering, uneven and varied time points, and time-independent covariates. Then topics will transition into more complex modeling variations, drawing from the following areas as time allows:

  • nonlinear models
  • spline models
  • time-dependent covariates
  • growth models for treatments and interventions
  • multidomain models
  • cohort-sequential models for planned missing data
  • second-order growth models
  • latent-difference score models
  • growth models with categorical data
  • growth mixture models
  • power analysis in latent growth models

Who should attend?

To benefit from this seminar, participants should have had exposure to statistical methods up through structural equation modeling, which includes topics such as measured variable path models, confirmatory factor models, latent variable path models, multisample covariance structure models, model identification, estimation, data-model fit assessment, and model modification/respecification. Familiarity with, or access to, Mplus software is not required for this seminar.


LOCATION, FORMAT AND MATERIALS

The class will meet from 9 am to 4 pm each day with a 1-hour lunch break at Temple University Center City, 1515 Market Street, Philadelphia, PA 19103. 

Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 


Registration and lodging

The fee of $995.00 includes all seminar materials. 

Lodging Reservation Instructions

A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $152 on May 19 and May 20. This location is about a 5 minute walk to the seminar location. In order to make reservations, call 203-905-2100 during business hours and use group code STA518. The room block will expire when it is full or on April 18, 2016. 


Outline

Foundations

  • quick review of SEM with measured and latent variables
  • latent means models
  • traditional longitudinal models framed in SEM (e.g., repeated measure models, panel models)
  • traditional linear latent growth models
  • varied reference points
  • uneven and varied time points
  • time-independent covariates
  • reparameterizing linear models

Beyond (as time allows)

  • nonlinear models
  • reparameterizing nonlinear models
  • spline models
  • time-dependent covariates
  • growth models for treatments and interventions
  • multidomain models
  • cohort-sequential models for planned missing data
  • second-order growth models
  • latent-difference score models
  • power analysis in latent growth models
  • growth mixture models
  • growth models with categorical data

COMMENTS FROM Hancock’s Structural Equation MOdeling: A second Course Seminar

“The content of this course was very applicable to my current work. I greatly appreciated the real-world in-class exercises and examples. These helped me envision how to work with my own data. Greg Hancock is an outstanding instructor who can explain complex topics to students with more and less sophisticated backgrounds. He also uses humor and personal anecdotes very effectively.”
  Tony Perez, Old Dominion University 

“The facilitator, Dr. Greg Hancock, struck the right balance between explaining the concepts behind the methods and getting participants exposed to technical application of the methods. The facilitator is a gifted instructor and a humorous person, which kept the classes interesting.”
  Anthony Waddimba, Bassett Research Institute 

“Greg is an excellent instructor. He brought the material alive with his real world examples and personal humor. He presented SEM models that I had previously believed were not possible in a concise manner. I highly recommend this course for anyone whose work deals with latent variable analysis.”
  Gerald Arnold, American Board of Internal Medicine (ABIM) 

“As a natural scientist I really enjoyed learning methods and techniques from the social sciences, and how they could be applied to my field.”
  Kris Johnson, US Forest Service 

“Greg Hancock is a wonderful instructor and if you are interested in advanced SEM techniques, I highly recommend this course!! Beyond being an expert in the field, his engaging pedagogy and genuine interest in your research and activities will make this course well worth your time and money.”
  John Barnshaw, American Association of University Professors 

“Dr. Hancock is very knowledgeable about the subject matter. He explains complex stat terms well. He is also attentive to students’ questions and helpful with inquiries.”
  Billy Bai, University of Nevada, Las Vegas