Statistical Analysis with Latent Variables

This page contains the streaming video of the
lectures of the course Statistical Analysis with Latent Variables taught by
Professor Bengt Muthén of the UCLA Graduate School of Education & Information
Studies.

All of the streaming videos (except Overview Parts 1-4 in Week 1) are stored as Quicktime movies and can be viewed
over a high speed internet connection (DSL, cable, campus connection) using the
Quicktime Player . If you are having troubles, see
our QuickTime Troubleshooting page.

The audio version of the lectures are available as mp3 files. There are two
ways that you can listen to these lectures. One way is via direct download
following the link to each of the mp3 files. The other way is via subscribing to
it as podcast. For instance, to listen to these lectures via iTunes, go to menu
Advanced->Subscribe to Podcast… and enter this url:

https://stats.idre.ucla.edu/stat/seminars/ed231e/latent_variables.xml

• Week 1 (April 5 & 7)
  • Lecture 1: Overview of course content. A general latent variable modeling
    framework.Overview Part 1,
    Overview Part 2, Overview Part
    3,
    Overview Part 4,
    Welcome
  • Lecture 2: Confirmatory factor analysis
• Week 2 (April 12 & 14)
  • Lecture 3: Multiple-group confirmatory factor analysis
  • Lecture 4: Structural equation modeling
• Week 3 (April 19 & 21)
  • Lecture 5: Introductory growth modeling
  • Lecture 6: Growth modeling, cont’d
• Week 4 (April 26 & 28)
  • Lecture 7: Growth modeling, cont’d
  • Lecture 8: Growth modeling, cont’d
• Week 5 (May 3 & 5)
  • Lecture 9: Introduction to modeling with categorical dependent variables
  • Lecture 10: Modeling with a preponderance of zeros (zero inflation)
• Week 6 (May 10 & 12)
  • Lecture 11: Discrete-time survival analysis
  • Lecture 12: Discrete-time survival analysis
    (cont’d)
• Week 7 (May 17 & May 19)
  • Lecture 13: Cross-sectional mixture modeling – LCA
  • Lecture 14: Cross-sectional mixture modeling – LCRA
• Week 8 (May 24 & 26)
  • Lecture 15: Longitudinal mixture
    modeling – LTA
  • Lecture 16: Longitudinal mixture modeling – GMM
  • Lecture 16.5:
    Longitudinal mixture modeling – GMM
    (cont’d)
  • Lecture 16.5.1:
    GMM Analysis
    Strategies (cont’d)
• Week 9 (June 2)
  • May 31 cancelled due to Memorial Day
  • Lecture 17: Latent variable modeling with missing data
• Week 10 (June 7 & 9)
  • Lecture 18: Multilevel latent variable modeling
  • Lecture 18.5: Monte Carlo
    Simulation Studies in Mplus
  • Lecture 19: Multilevel latent variable modeling cont’d
• FINALS Week (June 14)
  • Lecture 20: Multilevel mixture modeling
    (The video for this movie was overexposed so the video and audio quality is
    extremely poor, but is provided in the spirit that “something is better than
    nothing”.)