Introduction to Longitudinal Structural Equation Modeling

December 9-11, 2020
Online Webinar via Zoom
Instructors:
Dan Bauer and Patrick Curran
Software Demonstrations: Mplus, R, and Stata

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Course Description

Introduction to Longitudinal Structural Equation Modeling is a three-day workshop focused on the application and interpretation of structural equation models fitted to repeated measures data. The analysis of longitudinal data (i.e., the repeated measurement of the same cases over time) is fundamental in nearly all areas of social and behavioral science research. There are many structural equation models available for analyzing repeated measures data but the latent curve model is by far the most widely applied and will be the primary focus of this class. Topics include longitudinal designs, linear and non-linear latent curve models, predictors of growth, multivariate latent curve models, and observed and latent multiple group growth models (e.g., mixture models).

Course Schedule

Start date: December 09, 2020

End date: December 11, 2020

Start time: 09:00 a.m. EDT

End time: 05:00 p.m. EDT

Venue: Zoom Webinar

Email: info@curranbauer.org

Instructors

Dan BauerDaniel J. Bauer, Ph.D.

Dan Bauer is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won teaching awards from the University of North Carolina and from the American Psychological Association.  Endeavoring to make advanced statistical techniques more accessible, Dan has spent the last 15 years developing and teaching workshops on a variety of topics in both the United States and abroad, including multilevel modeling, mixture modeling, longitudinal data analysis, structural equation modeling, latent curve analysis, missing data analysis, measurement, and integrative data analysis. His research interests lie at the intersection of quantitative and developmental psychology, particularly the development of problem and health-related behaviors over childhood and adolescence. He has published over 65 scientific papers, served as Associate Editor for Psychological Methods, currently serves on the editorial boards of several journals, and has reviewed grants for the National Science Foundation, National Institutes of Health, and the Institute of Educational Sciences. He received an early career award from the American Psychological Association in 2009. For more details, see his academic web page.

Patrick CurranPatrick J. Curran, Ph.D.

Patrick Curran is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won teaching awards from UNC and from the American Psychological Association. Over the past 20 years Patrick has taught over 50 national and international workshops on structural equation modeling, multilevel modeling, latent curve analysis, longitudinal data analysis, and general linear modeling. He draws on experiences from his own program of research on high risk child development to guide and inform his quantitative teaching. Patrick’s program of research is primarily focused on the development and evaluation of statistical models of change over time, particularly as applied to studies of adolescent substance use. He has published over 70 scientific papers and chapters and has co-authored a text book on latent curve modeling with Ken Bollen. Patrick has served as Associate Editor for Psychological Methods and currently serves on the editorial boards of seven scientific journals. For more details, see his academic web page.

Course Details

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. Prior exposure to structural equation modeling is helpful, but we will also review core aspects of SEM at the start of the workshop. To have a stronger foundation in SEM, participants may wish to consider our Just-In-Time three-day streaming workshop in Structural Equation Modeling (available soon). To clarify, a prior class in SEM is not required to successfully participate in Longitudinal SEM, but can enhance the experience.

Software demonstrations will be provided in Mplus, R, and Stata. Note that R can be downloaded for free. While it is helpful to have some familiarity with Mplus, R, 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 topics in longitudinal structural equation modeling. We strive to strike an equal balance between core concepts of the underlying statistical models along with the practical application and interpretation of longitudinal 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 longitudinal SEM and to be able to thoughtfully apply these models 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 prior 2020 online offering of of Longitudinal SEM:

This was an excellent course and I will definitely enroll in more workshops in the future. Thanks for your hard work putting this together!

Lectures are very engaging, and the light-hearted rapport between Dan and Patrick helps keep even dense material approachable. Good use of examples in every chapter. Online format worked really well-- more affordable and easier to do!

The teaching style is engaging. I was not able to attend live due to other commitments, but had time over the next week-- having the flexibility to view the webinars on my own time (and be able to pause and think on the concepts) was invaluable.

The options for demonstrations in different software programs - recorded sessions have let me learn both MPlus (my preference) and R - so great!

Dan, Patrick, and Ethan are so knowledgeable and their excitement makes me excited to learn. I really appreciate the objectives before each lesson as well as a summary followed by an actual example.

I really liked the online delivery of this workshop (I wouldn't have been able to attend otherwise!). Everything was explained very clearly and the banter between the three of you was excellent!

The way that Dan and Patrick are able to effectively breakdown the key points of using these methods. Worth its weight in gold.

I appreciate all the hard work and thoughtfulness that Dan, Patrick, and Ethan put into this workshop. I learned a lot and had a lot of fun!

I really enjoyed this workshop. I didn't expect the Zoom format to be as good as it was. I particularly enjoyed the breakout sessions in the afternoons for specific software demonstrations. Also, having the videos available to view again was helpful.

What is Provided

Dan Bauer and Patrick Curran co-teach the workshop via Zoom and will alternate lecturing throughout the day. Participants will receive complete PDF copies of the course notes and the computer demonstrations as well as data and code for all examples. The PDFs are not time-limited and may be retained indefinitely but should not be distributed to others without obtaining prior permission.

Please see sample copies of the lecture notes (one chapter) and R demonstration notes (full copy) from our 5-day SEM class. Mplus and Stata versions parallel the R demonstration notes.

Interactions with Instructors

Participants can ask text-based questions using a Zoom function that will be monitored by CBA staff and conveyed to the instructor. If a question cannot be answered during lecture, a text response will be provided at a later time.

Connectivity Requirements

Because participants are receiving the stream from Zoom and not broadcasting video images back, the connectivity requirements are minimal. A minimum of 150kbps (kilobytes per second) is required to participate in a video webinar, and this can be wired or wireless. Given typical home internet connections or personal WiFi access, these requirements are quite low. For example, it is recommended that a 3000kbps (or 3mbps, megabytes per second) connection be used to stream a movie on Netflix. A typical WiFi hotspot on a typical cell phone is 20-30mbps, thus any standard internet connection should allow for uninterrupted participation in the webinar. See https://www.speedtest.net/ to evaluate your own connection speed. Note that a typical source of connectivity problems in the home is linking the device to the WiFi broadcast unit, so be certain your device is has uninterrupted lines of site to the wireless modem; see, e.g., https://www.familyhandyman.com/smart-homeowner/9-simple-tips-for-faster-wi-fi/

Daily Schedule

Live-stream lectures will begin at 9:00 a.m. and finish at approximately 4:00 p.m. Eastern Time (US) each day. Computer demonstrations will be provided from approximately 4:00 p.m. to 5:00 p.m. Eastern Time (US), with separate breakout meetings for Mplus, R, and Stata.

There will be 15-minute morning and afternoon breaks and a one hour lunch break, the exact times of which are determined during lecture. Local time zones within which the participant is connected must be adjusted to correspond to Eastern Standard Time.

Availability of Recordings

The live-stream does not have DVR-like controls and thus cannot be paused or rewound during the session itself. However, full recordings of the live-stream will be available to all participants for 14 days following the completion of the workshop. The recordings cannot be saved by the participant and will not be available after the 14-day period.

Technical Support

CBA is not able to provide technical support for end-user issues. As such, participants are fully responsible for connectivity that supports the live-stream of audio and video. Information will be provided about the minimum required bandwidth and methods for testing connectivity. However, in the low probability that a participant is not able to connect, there will be access to the recorded sessions for 14 days following the completion of the workshop.

Tuition Reduction Opportunities

We offer reduced-price registrations 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 choose the student rate when beginning the registration process at the top of the page. Confirmation of student status may be requested at a later time.

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 fully refund registration fees, minus transaction fees, for cancellations made with one week or more notice prior to the event. Registration fees are non-refundable if a cancellation is made less than one week before the event.

Syllabus

Chapter 1. Introduction and Review of SEMs
1.1 Introduction and Organization of the Workshop
1.2 Longitudinal Designs
1.3 Review of Structural Equation Models

Chapter 2. The Unconditional Linear Latent Curve Model (LCM)
2.1 Defining a Latent Growth Curve
2.2 Latent Growth Curves as a Confirmatory Factor Model
2.3 Alternative Metrics of Time

Chapter 3. Nonlinear and Conditional Latent Curve Models
3.1 Modeling Nonlinear Trajectories: Quadratic, Piecewise, and Freed-Loading Models
3.2 Time-Invariant Covariates (TICs): Defining Main Effects and Interactions
3.3 Probing and Graphing Effects Between TICs and Growth Factors

Chapter 4. Multivariate Latent Curve Models
4.1 Time-Varying Covariates: Defining Contemporaneous and Lagged Effects
4.2 The Fully Multivariate Latent Curve Model
4.3 Self-Study: Advanced Multivariate Models

Chapter 5. Modeling Population Heterogeneity: Part 1
5.1 Population Heterogeneity in the Conventional LCM
5.2 The Multiple Groups Growth Model
5.3 Extensions of Multiple Groups LCM

Chapter 6. Modeling Population Heterogeneity: Part 2
6.1 Growth Mixture Models: Theory and Specification
6.2 Class Enumeration
6.3 Self-Study: Model Sensitivity

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