Applied Quantitative Analysis II
Linear regression review, GLMs, Sampling & Weighting, Introduction to Causal Inference, Multiple Imputation, and other Misc topics
Lab materials for Applied Quantitative Analysis II (Instructor: Mike Hout) taught in 2018 at NYU. Slides were prepared for concepts/methods that students found difficult to understand; most instructions and explanations are annotated in the do-files.
- Lab 10 - Comparing Coefficients of Logit/Probit Models: Heterogeneity in Latent Scales
- Lab 9 - Measurement Error, Instrumental Variables, and Multiple Imputation
- Lab 8 - Causal Inference (cont.) & Panel Data
- Lab 7 - Introduction to Causal Inference: Ignorability, SUTVA, and Propensity Scores
- Lab 6 - Sampling and Weighting
- Lab 5 - Imputation of Top-coded Income Variable using Pareto Distribution, Scatterplot Smoothing, Regression Splines, and Information Criteria
- Lab 4 - Ordered Logistic Regresssion (cont.), Generalized Ordered Logistic Regression
- Lab 3 - Latent Variable Formulation of Logistic/Probit Regressions, Ordered Logistic Regression
- Lab 2 - Review of Interactions, Polynomials, and Logistic Regression (cont.)
- Lab 1 - Review of Linear Regression and Logistic Regression