Structural Equation Modeling: A Second Course

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

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Structural equation modeling (SEM) is a versatile analytical framework for estimating and assessing models that describe relationships among both measured and latent variables.  Common examples include measured variable path models, confirmatory factor models, and latent variable path models. These models subsume methods based on the traditional general linear model such as multiple regression and analysis of variance.

This seminar goes beyond introductory SEM to cover more advanced methods that enable researchers to address their current modeling questions more effectively and also to focus on entirely new research questions. After a review of SEM basics, we will cover real data challenges (e.g., missing data, nonnormality, categorical data), mean structure models for measured and latent variables, latent growth curve models, and power analysis in SEM. The style of instruction is designed for participants with a variety of content backgrounds.  Examples will use popular SEM packages, with an emphasis on Mplus.


WHO SHOULD ATTEND

The course will benefit applied researchers, analysts, and students interested in enhancing their understanding of SEM and developing their application skills.  Participants are assumed to have been exposed to introductory SEM, such as that offered through an in-depth workshop or a typical university course, including such topics as measured variable path models, confirmatory factor models, latent variable path models, multigroup models, identification, estimation, fit, and SEM software implementation.


Seminar Outline

  • Review of SEM and software basics
  • Real data challenges
    • missing data
    • nonnormality
    • categorical data
  • Mean structure models for measured and latent variables
  • Latent growth curve models
  • Power analysis in SEM

LOCATION AND MATERIALS 

The course meets 9 a.m. to 4 p.m. on Friday, April 25 and Saturday, April 26 at Temple University Center City, 1515 Market Street, Philadelphia, PA.

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 $895.00 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 $142 per night for a Standard room. 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 identify yourself by using group code STA424. For guaranteed rate and availability, you must reserve your room no later than March 24, 2014.


RECENT COMMENTS FROM PARTICIPANTS

“This course was easily the best I’ve ever been to, and I attribute that success largely to Dr. Hancock, the instructor. He took the time to explain complex material in a way that made it seem easy, and he did it without sounding condescending. I was able to learn things that are immediately applicable to my research, and I’d sit through a 3rd and 4th course with Dr. Hancock in a heartbeat.”
     Chris Rakes, University of Maryland, Baltimore County

“Dr. Hancock’s presentations were practical and accessible, highly valuable and useful for professionals looking to update their analytic skills in an efficient manner. This was an excellent experience.”
     Jonathan G. Tubman, American University

“A skilled and experienced teacher. Able to handle complex questions on-the-fly. Great review of underlying concepts prior to diving into the more complicated examples.”
     Mark Trentalange, Yale Program on Aging

“Greg explains difficult concepts well, building up to them efficiently.”
  Regina McNally, University of Limerick 

“This course is a nice extension of the first SEM course. Emphasis is on Mplus. Dr. Hancock provides a different approach to data analysis than is commonly taught in Statistic classes. It is very informative and provides the conceptual picture, Mplus programs with explanation, and Mplus output with interpretations.”
  Stephanie Pugh, American College of Radiology 

“An excellent course for those who have some background and experience in SEM. Greg was a knowledgeable and approachable instructor.”
  Christopher Lake, University of Minnesota