The workshop will focus on the theory and methods for missing data analysis and its application to latent variable models. Topics include maximum likelihood estimation under missing data, mean score theorem, EM algorithm, imputation, fractional imputation, multiple imputation, propensity scores, doubly robust estimation, and non-ignorable missing data.

Outline:

1. Basic Theory for missing data (80 minutes)
2. Imputation (80 minutes)
3. Propensity score approach (80 minutes)
4. Advanced topics (80 minutes)

Note:

Session 1: (9:00-10:20)

Coffee break: (10:20-10:40)

Session 2: (10:40-12:00)

Lunch break: (12:00-13:30)

Session 3: (13:30-14:50)

Coffee break: (14:50-15:10).

Session 4: (15:10-16:30).