This is the page is dedicated to the lab session of the course Applied Quantitative Analysis-II at New York University.
AQA2 is a graduate-level core quantitative method course for the Master program Applied Quantitative Research at NYU Sociology. Professor Mike Hout is the main instructor, and I am the teaching assistant.
- Review of regression analysis -- OLS, Logit, Probit basics
- Generalized linear models -- Logit, Probit regression models, interpreting odds ratios
- Interpreting regression results -- marginal effects of linear/non-linear equations, interaction effects
- Latent variable regression -- single index model
- Discrete choice model -- Ordered, Multi-nomial Logit/Probit models
- Non-parametric estimations -- Kernel methods, Local Polinomials, Spline function
- Regression partitioning and decompositions -- direct/indirect effects, omitted variable bias
- Missing data issues -- MAR, MACR, MNAR, multiple imputations
- Treatment effects -- counterfactuals, PS-matching
- Panel data -- Pooled regression, GLS, Fixed/random effects, hierarchical models
- Instrumental variables -- LATE, 2-stage-least-sqaures
- Special topics: Time-series with covid-19 data