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Dave Armstrong
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LaTeX Workshop
These are the notes and all files required to successfully compile the handouts from the workshop on Monday, June 22, 2009.[LaTeX Files]
Introduction to R
These are the handouts and R code from the five-day Introduction to R workshop offered from June 23-30, 2009.
     Lecture 1: Getting to know R/Data Types [handout][R-code]
     Lecture 2: Data Types/Models [handout][R-code]
     Lecture 3: Graphs (Traditional) [handout][R-code]
     Lecture 4: Repeated Calculatoins [handout][R-code]
     Lecture 5: Repeated Calculations and Lattice Graphs [handout][R-code]
Regression III
Instructor:
Dave Armstrong
University of Oxford (Political Science)
e: davearmstrong(dot)ps(at)gmail.com
Teaching Assistant:
Matthew Painter
Ohio State University (Sociology)
e: painter(dot)63(at)sociology(dot)osu(dot)edu
 
These are slides and materials from the Regression III course taught in the Summer of 2008 at the ICPSR Summer Program in Quantitative Methods.  I taught a condensed version of this course using Stata at the Essex Summer School in Data Analysis and Collection at the University of Essex in the Summer of 2008.  Slides and materials pertaining to that class can be found here.
 
Course Materials: Syllabus
Lecture 1: Introduction [slides] [R-code] [Data and R-code zip)]

Lecture 2: OLS [slides] [R-code]

Lecture 3: Graphs in R [slides] [R-code] [Data and R-code (zip)]

Lecture 4: Effective Model Presentation [slides] [R-code] [Data and R-code (zip)]
     Homework 1 [data]

Lecture 5: Interactions and Density Estimation [slides] [R-code] [Data and R-code (zip)]

Lecture 6: Linearity [slides] [R-code]

Lecture 7: Non-linearity and Splines [slides] [R-code]

Lecture 8: Splines and GAMs [slides] [R-code]

Lab 1: Non-Linearity and Interactions: [ Handout ][R-code] [ dumdiffs in R][Data]
Lecture 9: Generalized Additive Models

Lecture 10: Outliers and Influential Data

Lecture 11: Robust Regression

Lecture 12: Non-Normality and Heteroskedasticity

Lecture 13: Multilevel Data: Introduction
Lecture 14: Multilevel Change Models (by Matthew Painter)
Lecture 15: Multilevel Data and Models
Lecture 16: Models for TSCS Data
Lab 2: Multilevel/TSCS Stuff, Other Various Topics