Psychometrics and Causal Inference in Stata

Free for registered participants to attend

Schedule:
8:30 – 9:30am	Basic Stata Commands
9:30 – 10:30am	Basic Stata Estimation Commands
10:45 – 11:45am	Intro to Psychometrics with Stata: Topics include reliability, Cohen’s kappa statistic, canonical correlation, Cronbach’s alpha, exploratory factor and confirmatory factor analysis, factor rotations, multivariate analysis of variance (MANOVA), contrasts and pairwise comparisons, structural equation modeling (SEM), item response theory (IRT), and latent class analysis (LCA).
1 – 2:15pm	Intro to Causal Inference and Treatment Effects Basic concepts of causal inference including counterfactuals and potential outcomes are introduced. Demonstration of Stata’s -teffects- suite of commands to fit causal models using propensity score matching, inverse-probability weighting, regression adjustment, “doubly-robust” estimators that use a combination of inverse-probability weighting with regression adjustment, and nearest-neighbor matching.
2:30 – 4pm	Causal Inference for Complex Observational Data Concepts in missing data such as missing at random (MAR), missing not at random (MNAR), and unobserved confounding are introduced. This talk will demonstrate how to use standard maximum likelihood estimation to fit extended regression models (ERMs) that deal with all of these common issues alone or simultaneously.