Donald Green
PL504 Course Materials
o Problem Set 1: Solution Set using GAUSS
o Problem Set 1: Solution Set (Binomial, individual level data) using EXCEL
o Problem Set 1: Solution Set (Binomial, grouped data) using EXCEL
o Problem Set 1: Solution Set (Poisson likelihood) using EXCEL
o Problem Set 1: Solution Set (Normal likelihood) using EXCEL
· Lecture Notes
o Week 1: Maximum Likelihood for the Masses
o Week 2: Sampling Distributions
o Week 3: MLE and Linear Regression
o Week 4: MLE details
o Week 5: Binary Response Models
o Week 7: Truncation and Censoring
o Week 10: Covariance Algebra
o Week 11: Instrumental Variables Regression
o Week 13: Panel Data
· Gauss Primer Links
· Instructional Examples
o Regression Analysis Handouts
o Instrumental Variables Example Handout 1
o Instrumental Variables Example Handout 2
o Instrumental Variables Example: SPSS Syntax
o Mathematica Does Calculus For You: INPUT
o Mathematica Does Calculus For You: OUTPUT
o Illustration: Consistency of OLS
· Measurement Error: Consequences and Correctives
· 2SLS Practicum: Campaign Finance
· Data for Campaign Finance Example
o Bootstrapping and Simulation
o
Optimization
Example: Example with Binomial
Data
o Newton-Rapheson Spreadsheet Example: Binomial Data
o Optimization Example: Binomial Data, with Logit and Probit
o Optimization Example: Logistic Regression Monte Carlo
o Optimization Example: Probit Monte Carlo
o Optimization Example: Probit Monte Carlo with Index Variable Specification
o Optimization Example: Logistic Regression with Grouped Data
o Optimization Example: Logistic Regression with Individual Data
o Optimization Example: Logistic Regression Monte Carlo with Random Effects
o
How
Omitting Uncorrelated Variables Biases Logistic Regression
o
Graph:
moving from Log-odds to Percentages
o Spreadsheet: moving from logit, ordered logit, and multinomial logit to percentages
o Optimization Example: Least Squares Regression
o Optimization by means of a Grid Search: Nonlinear Least Squares Regression
o Optimization Example: MLE for Normal Regression
o Optimization Example: MLE for Normal Nonlinear Regression
o Optimization Example: MLE for Heteroskedastic Regression
o Optimization Example: MLE for Heteroskedastic Regression using Infant Mortality in Africa
o
Optimization
Example: MLE for Heteroskedastic Regression using
Infant Mortality: line search
o Optimization Example: MLE for Truncated Regression
o Optimization Example: MLE for Censored Regression
o Optimization Example: MLE for binary data: Hamden turnout example
o Optimization Example: MLE for binary data: Hamden data
o Alternative methods of calculating regression estimates and standard errors
o Alternative computational approaches to weighted least squares
o Simulating Poisson Random Variables
o Simulating Poisson Regression
o Poisson regression: Supreme Court appointments
o Poisson regression: Hate Crime Data from NYC
o Poisson regression: Analysis using Hate Crime Data from NYC
o
Comparing Poisson
and Negative Binomial Distributions
o
Simulating
Negative Binomial I Regression with Constant Dispersion
o Simulating Negative Binomial II Regression with Mean-Related Dispersion
o Negative Binomial Regression with Constant Overdispersion: Hate Crime Data
o Negative Binomial Regression with Overdispersion Proportional to the Mean: Hate Crime Data
o Stata Dataset: Hate Crime Data from NYC
o Normal-Exponential regression: Analysis using Hate Crime Data from NYC
o Ordered and Unordered Logistic Regression
o Simulating Panel Data: Pooled TSCS OLS vs. Fixed Effects
o Simulating Panel Data: Pooled TSCS Random Effects vs. Fixed Effects
o
Simulating
Panel Data: Random Effects vs. Fixed Effects: Bias in RE when intercepts
are correlated with X
o Analysis of Panel Data: Greene’s Example 14.1: Stata Data File
o
Analysis
of Panel Data: Greene’s Example 14.1: Stata Do
File
o Analysis of Panel Data: Greene’s Example 14.1: Gauss Data File
o
Analysis
of Panel Data: Greene’s Example 14.1: Gauss Program
o Analysis of Panel Data: Greene’s Table 13-2: Stata Data File
o
Analysis
of Panel Data: Greene’s Table 13-2: Stata Do
File
o Simulating Time-Series Data: Eviews
o Spatial/temporal Autocorrelation Models: Simulation and ML Estimation
o MLE vs. method of moments example
o Introduction to LISREL: Example 1
o Introduction to LISREL: Example 2
o Introduction to LISREL: Example 3
o Introduction to LISREL: Example 4
o Introduction to LISREL: Example 5
o Introduction to LISREL: Mood Study 2: Random Error
o Introduction to LISREL: Mood Study 2: Nonrandom Error
o Introduction to LISREL: Hispanics: Random Error
o Introduction to LISREL: Hispanics: Nonrandom Error
o How Multiple Measures Enhance the Robustness of Lisrel Models
o Checking Model Identification Using LISREL
o
Illustration
of reciprocal causation: Excel
o Some helpful links: meta analysis
o Some helpful links: robust regression
comments: Donald
Green.
Web Site: research.yale.edu/vote
Copyright © Yale University, 2005