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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 Thursday and Friday June 24-25, 2010.[LaTeX Files]
Introduction to R
These are the handouts and R code from the Introduction to R workshop offered from July 20-30, 2010.
     Lecture 1: Getting to know R/Data Types [handout][Data and R-code (zip)]
     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 Wisconsin--Milwaukee (Political Science)
e: armstrod@uwm.edu

Teaching Assistant:
Matthew Painter
Ohio State University (Sociology)
e: painter(dot)63(at)sociology(dot)osu(dot)edu
 
This is the website devoted to the Regression III course for the ICPSR Summer Program in Quantitative Methods. In preparation for the upcoming Summer, the links to course materials have been removed (and will be replaced when appropriate). If you have any questions, please don't hesitate to ask.
 
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] [Data and R-code (zip)]

Lecture 4: Effective Model Presentation [slides] [R-code]
     Homework 1 [data]

Lecture 5: Linearity[slides] [R-code] [Data and R-code (zip)]

Lecture 6: Non-linearity and Splines [slides] [R-code] [Updated Splines Code ] [B-Spline Stuff]

Lecture 7: GAMs [slides] [R-code] [Data and R-code (zip)]

Lab 1: Non-Linearity and Interactions [Handout, Answers] [Data] [R-code]
     Homework 2

Lecture 8: Outliers and Influential Data [slides] [R-code] [Data and R-code (zip)]

Lecture 9: Robust Regression [slides] [R-code] [Data and R-code (zip)]

Lecture 10: Non-Normality and Heteroskedasticity [slides] [R-code] [Data and R-code (zip)]

     Homework 3 [data]

Lecture 11: Multilevel Data and Models [slides] [R-code]

Lecture 12: Models for Time-Series Cross-Sectional Data [slides] [R-code] [Data and R-Code (zip)]
Lecture 13: Missing Data and Multiple Imputation [slides] [R-code] [Data and R-Code (zip)]
Lab 3: Multilevel/TSCS Stuff, Other Various Topics [Handout, Answers] [Data] [R-code]