Latent Curve Models

Our workshop is designed for graduate students, post-doctoral fellows, faculty, and research scientists from the behavioral, social, and health sciences. Although not essential, prior exposure to structural equation modeling (SEM) is helpful to enhance understanding in the class. Participants with no prior exposure to SEM may wish to consider taking our free pre-recorded workshop Introduction to Structural Equation Modeling. For those who simply need a refresher or want a quick overview, we also provide a brief pre-recorded review of SEM that can be viewed in advance of the class (available upon enrollment, through My Workshops on your profile menu). To clarify, a prior class in SEM is helpful but not required to successfully participate in the current class.

Chapter 1. Introduction to the Analysis of Change
1.1 Overview and Structure of the Workshop
1.2 Two Time Point Designs & Raw Change Scores

Chapter 2. The Unconditional Linear Latent Curve Model
2.1 Defining a Latent Growth Curve
2.2 Latent Growth Curves as a Confirmatory Factor Model
2.3 Thinking More Closely About Time: Zero Point & Spacing

Chapter 3. Nonlinear Latent Curve Models
3.1 Implications of Linearity
3.2 Higher-Order Polynomial Growth
3.3 Piecewise Splines and Freed Factor Loadings

Chapter 4. Time-Invariant Covariates & Conditional Latent Curve Models
4.1 Time-Invariant Covariates: Predictors of Growth
4.2 Main Effects and Interactions with Time
4.3 Probing and Plotting Predictors of Growth

Chapter 5. Time-Varying Covariates & Multivariate Latent Curve Models
5.1 Time-Varying Covariates: Contemporaneous and Lagged Effects
5.2 The Fully Multivariate Latent Curve Model
5.3 Survey of Advanced Multivariate Model Structures

Chapter 6. Model Extensions and Next Steps
6.1 Non-Normality and Robust Methods of Estimation
6.2 Observed Population Heterogeneity and Moderated LCMs
6.3 Survey of Model Extensions

Livestream lectures will begin at 10:00 a.m. and finish at approximately 3:30 p.m. Eastern Time (US) each day. There will be 10-minute morning and afternoon breaks and a 45-minute 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 Time (US).

Software demonstrations will be pre-recorded and available 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.

Dan Bauer and Patrick Curran co-teach the workshop live via Zoom and will alternate lecturing throughout the day. Recordings of the lectures are posted at the end of each day to allow participants to catch up who miss portions of the livestream or wish to review. Computer demonstrations are provided in R, Mplus, and Stata via pre-recorded videos.

Participants receive access to the livestream, one-year of access to recorded lecture and demonstration videos, downloadable 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 and Mplus demonstration notes from our 3-day Introduction to SEM class. R and Stata versions parallel the Mplus demonstration notes.