quant3materials

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Quantitative Methods for Political Science 3

This repository contains a selection of recitation materials prepared by Pablo Barberá for the PhD-level course "Quantitative Methods for Political Science 3", taught by Prof. Nathaniel Beck in the Fall of 2013 at New York University.

Maximum likelihood

• (Re-)introduction to R
• Recovering the parameters of a Poisson and a Beta distribution using maximum likelihood
• Recovering the parameters of a exponential distribution using maximum likelihood
• Probit regression and quantities of interest
• Probit/Logit and marginal effects
• Ordinal probit and marginal effects
• Identification in logit regression
• OLS vs Poisson regression

Duration models

• Duration models with R

Time-series analysis

• Introduction to time-series with R
• Impulse/unit response functions for ADL model
• Time-series and stationarity
• Cointegration and error-correction models

Bayesian statistics

• Accept-reject sampling of a beta distribution
• Bayesian samplers (grid sampling, Metropolis-Hastings, Gibbs, Hamiltonian Monte Carlo)
• Bayesian Poisson Regression
• Bayesian Probit Regression
• Bayesian Hierarchical Regression
• Introduction to Multilevel Regression with Poststratification
• Introduction to Item-Response Theory models
• Introduction to High-Performance Computing
• More advanced examples of IRT models