Structural Equation Modeling

May 15 to May 19, 2017
Chapel Hill, North Carolina
Instructors: Dan Bauer and Patrick Curran
Software Demonstrations: Mplus and Stata


Structural Equation Modeling is a five-day workshop focused on the application and interpretation of statistical models that are designed for the analysis of multivariate data with latent variables. Although the traditional multiple regression model is a powerful analytical tool within the social sciences, this is also highly restrictive in a variety of ways. Not only are all variables assumed to have no measurement error, but it is also limited to a single dependent variable with unidirectional effects. The structural equation model (SEM) generalizes multiple regression to include multiple dependent variables, reciprocal effects, indirect effects, and the estimation and removal of measurement error through the inclusion of latent variables. The SEM is a general framework that allows for the empirical testing of research hypotheses in ways not otherwise possible. In this workshop we provide a comprehensive exploration of the SEM with topics ranging from introductory to advanced, as described in detail below.

Who Should Attend and Software Considerations

Our workshop is designed for graduate students, post-doctoral fellows, faculty, and research scientists from the behavioral, social, and health sciences. Although it is recommended that participants have a working knowledge of the general regression model, these core concepts will be reviewed at the beginning of the workshop.

Software demonstrations will be provided in separate Mplus and Stata break-out groups at the end of each day (you choose which to attend). Electronic copies of the full set of demonstrations in AMOS and a subset of demonstrations in LISREL are also provided but these are not covered in class. While it is helpful to have some familiarity with Mplus or Stata, this is not necessary. The lectures which constitute the majority of the workshop are software-independent.

The Goals of the Workshop

Our motivating goal is to provide an intense yet enjoyable instructional experience that focuses on a large number of both introductory and advanced topics in structural equation modeling. We strive to strike an equal balance between core concepts of the underlying statistical model along with the practical application and interpretation of SEMs fitted to real empirical data. Our workshop is designed to provide participants with the materials and instruction needed to both develop a real understanding of the SEM and to be able to thoughtfully apply a variety of basic and advanced SEMs to their own data.

Reviews From Past Participants

In an effort to continually improve our instruction we obtain student evaluations with each course offering. Here is a sample of reviews from our 2016 SEM workshop:

    One of the few stats workshops to keep my full attention. Perfect balance of core mathematical concepts, statistical equations, and application. Dan and Patrick make complex topics fun and accessible. The workshop materials are worth the cost of the workshop!

    For SEM, it’s even better than the “gold standard” training workshop. Run and go for it at all cost.

    It’s awesome! Wonderful mix of breadth and depth. Provided a detailed framework as well as strong examples and help with applications.

    Patrick and Daniel present the material in a very digestible way and create an open atmosphere for questions and learning but not at the expense of content. An incredible learning experience.

    Mplus/Stata manuals — wow, wow, wow!

Read more…

What is Provided

Dan Bauer and Patrick Curran co-teach the workshop and alternate lecturing throughout the day. We provide approximately 35 hours of total lecture time as well as a bound copy of the course notes and the computer demonstrations (approximately 600 pages total). Although there is not a hands-on computer lab component to this workshop, we provide extensive live demonstrations in Mplus and Stata and distribute the data and syntax files for all examples. Further, participants are welcome to bring personal laptop computers to follow along with the software demonstrations or to work on their own data applications.

Please see sample copies of the lecture notes and Mplus notes. A parallel version of the computer notes is provided using Stata. Note that an electronic version of the full computer notes is also provided for AMOS, as well as key examples in LISREL; however, in-class demonstrations are provided only for Mplus and Stata.

All participants also have the opportunity to sign up for individual consulting meetings on Wednesday, Thursday, or Friday.

A continental breakfast and continuous snack and beverage service are also provided each day.

Learn more about what makes our training unique…

Daily Schedule

Each day begins at 8:30 with a free continental-style breakfast provided at the conference center. The morning session is from 9:00 to 12:15 and includes a mid-morning break. Lunch is from 12:15 to 1:30 and attendees can select from a large number of restaurants in downtown Chapel Hill. The afternoon session continues from 1:30 to 3:30 and includes a mid-afternoon break. Finally, on Monday through Thursday, two break-out sessions each led by Dan and Patrick are held from 3:30 to 5:00 that are focused on the demonstration of fitting models in either Mplus or Stata. The day concludes at 5:00 except on the final day which concludes at approximately 3:30 to allow for afternoon travel. Finally, we will host a happy hour on Monday at 5:00 with appetizers and drinks at The Back Bar which is located on the same floor as the lecture hall.

Facilities and Accommodations

We are very pleased to hold our workshop in the Great Room located at the Top of the Hill Restaurant and (yes) Brewery. The Great Room is located at 100 East Franklin Street at the historic intersection of Franklin Street and Columbia Street in downtown Chapel Hill and is just steps from the campus of the University of North Carolina. The Great Room is housed in the space once occupied by the legendary Carolina Theater and is characterized by soaring ceilings, hard wood floors, red brick walls, and flowing natural light.

We have reserved a block of reduced-rate rooms at the Hampton Inn for workshop participants that will be available until April 14th or the block is sold out (if you prefer to make a reservation by phone, please indicate you are with the Curran-Bauer Analytics group). Set in the heart of Chapel Hill/Carrboro, the Hampton Inn is less than one mile from the Great Room and it is approximately a 15 minute walk from the hotel to the meeting room. Chapel Hill also offers free buses and the J-line bus route stops right in front of the hotel and then at Franklin and Columbia, the intersection nearest the Great Room.

There are also many additional local hotels available, some within walking distance and others which offer free shuttle service to and from the Great Room.

Tuition and Registration

Tuition for the five-day workshop is $1795 per registrant. We offer a fixed number of reduced-price registrations of $1295 for graduate students who are actively enrolled in a recognized masters or doctoral training program. No application is necessary to qualify for the student tuition rates; simply select “student” when beginning the registration process. Confirmation of student status may be requested at a later time. We will maintain a waitlist once the student seats are filled.

We also offer a 10% reduction in total tuition when enrolling in two or more workshops. Simply proceed through the registration process and enter the code multi when prompted.

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Support for Junior Scholars from Under-Represented Groups

We are fortunate to have the opportunity to work in collaboration with the Society of Multivariate Experimental Psychology (SMEP) to provide a limited number of financial awards to students from under-represented groups to attend methodological workshops. These awards are made to qualifying students and post doctoral fellows with available funds of up to $1000 per student. Please see Support for Students from Underrepresented Groups to Attend Methodological Workshops for full details on both of these sources of support.

Cancellation Policy

Curran-Bauer Analytics will refund registration fees for cancellations made with two weeks or more notice prior to the event. For credit card registrations, 10% will be deducted from the refund to pay transaction fees imposed by the credit card companies; there is an industry-imposed 4.95% charge to book the registration and another 4.95% to cancel the registration. For check or purchase order registrations, registration fees will be refunded in full. Registration fees are non-refundable if a cancellation is made less than two weeks before the event.


Chapter 1. Introduction, Background, & Multiple Regression
1.1 Introduction
1.2 A Brief Introduction to Matrix Algebra
1.3 A Brief Introduction to Maximum Likelihood
1.4 Linear Regression as a Structural Equation Model
1.5 Path Diagrams
1.6 Limitations of the Multiple Regression Model

Chapter 2. Path Analysis: Introduction
2.1 The Path Analysis Model
2.2 Mean and Covariance Structures
2.3 Model Identification
2.4 Model Estimation

Chapter 3. Path Analysis: Advanced Topics
3.1 Assessing Model Fit
3.2 Model Comparisons
3.3 Model Respecification and Modification Indices
3.4 Testing Direct and Indirect Effects
3.5 Assumptions

Chapter 4. Confirmatory Factor Analysis
4.1 Exploratory Factor Analysis
4.2 Confirmatory Factor Analysis
4.3 Issues and Extensions

Chapter 5. Structural Equation Models with Latent Variables
5.1 Introduction to Structural Equation Models
5.2 Fitting and Evaluating Structural Equation Models
5.3 Additional Considerations: Estimation with Non-normal Distributions, Computing Power, and Equivalent Models (Self-Study)

Chapter 6. Multiple Groups Models
6.1 Modeling Heterogeneous Populations
6.2 Multiple Groups CFA
6.3 Structural Invariance

Chapter 7. SEM with Categorical Indicators
7.1 Discrete Dependent Variables
7.2 The Underlying Latent Variable Approach: Regression
7.3 The Underlying Latent Variable Approach: SEM
7.4 The Generalized Linear Modeling Approach: Regression
7.5 The Generalized Linear Modeling Approach: SEM

Chapter 8. Latent Growth Curve Analysis
8.1 The Concept of a Latent Growth Curve
8.2 Latent Curves as a Confirmatory Factor Model
8.3 Alternative Functional Forms of Growth: Linear versus Quadratic Trajectories
8.4 Time-invariant Predictors of Growth
8.5 Survey of Advanced Latent Curve Modeling Extensions and Applications

Please contact us either via email or by phone (919.533.9817) if you need any additional information or have any further questions.