Generalized Linear Models in R
Instructor: John Ahlquist
Lab Instructor: Carlisle Rainey
Lab Time: Friday, 1:25-3:00
Lab Place: HCB 302
Schedule
Note: I've changed my website since teaching this class, so some of the urls referenced in the code won't work.
| Lab | Title | Topics | Lab Materials | Data Files | Other Potentially Useful Files |
| 1 | Introduction to R Programming | Libraries, some programming technicalities, loading data, summarizing data, linear regression, some LaTeX tips |
Lab 1, Presentation |
anes1992.dta, anes1992.csv | Code for histograms,some humor,detailed intro |
| 2 | Graphics in R | Indexing and loops, the plot() function in detail, other graphics functions. |
Lab 2, Exercise, Presentation |
None | margins, colors, complete plot |
| Maximum Likelihood Estimation in R |
Introduction to Zelig,functions, optimization | Lab 3, Zelig example, Presentation |
None | Normal regression in Zelig, simulation paper |
|
| 4 | Logit and Probit in R | Zelig for logit and probit,plotting functions,plotting inferences | Misc, Analysis |
CSES subset |
Logit and probit regression in Zelig |
| 5 | Evaluted Models of Binary Variables |
Gradients for optim(),cross-validation in R,ROC and BIC for logit models | gradient, cross-validation, ROC curves |
None | |
| 6 | Ordered Logit and Probit in R | Ordered logit and probit,categorical explanatory variables,contrasts | Lab 6 | None | |
| 7 | Unordered Logit and Probit in R | Zelig for unordered categorical models, Q&A |
None | None | |
| 8 | Poisson Regression in R | Zelig for Poisson regresson,Q&A | None | None | |
| 9 | Multi-Equation Models in R | Zelig for multi-equation models,Q&A | John Ahlquist's sample code, simulating distributions |
||
| 10 | Multiple Imputation in R | Amelia, other software,Q&A for class projects | Amelia |
Resources for R
| Link | Description |
| Wikipedia on R |
If you are like me, you turn to Wikipedia as an introduction to people, ideas, math, and software. |
| Wikibooks on R programming |
Excellent source on programming in R with lots of examples. Organized by topic as well. |
| Simon Jackman's Take on R |
Pages 20-22 of The Political Methodologist, vol, 11, no 2. Also see the two articles on computing with R that follow Jackman's piece. |
| Installing R and Text Editors |
This .pdf gives an excellent set of instructions for downloading and installing R and choosing a text editor. It has equally good discussions of R for Windows and Mac. |
| Quick-R | Quick-R is a website designed to help users of other statistical packages such as Stata, SAS, and SPSS, transition smoothly into R. This site does assumes little, but some knowledge of statistics. |
| R manuals | These are the official manuals for the R packages. These are probably too technical for new R users, but after becoming more familiar with the software, these are very useful. |
| A Course on R |
An online course maintained by John Fox designed to introduce students to R. |
| Google's R Style Guide |
A set of stylistic rules for writing R scripts. These rules are designed by the R user community atGoogle. Using a consistent style makes your code easier to read andcorrect. |
| Text editor instructions |
Andrew Gelman's instruction for setting up text editors for R in Windows |
| Zelig | Gary King's software that allows estimating and working with inferences from many common models in political science. See Imai, King, and Law (2008). |
Resources for LaTeX
| Link | Description |
| sample2.pdf, sample2.tex |
The .pdf gives lots of useful tips as well as code to create LaTeX documents. The .tex files gives the LaTeX code used to produce the .pdf. Courtesy of Matt Golder. Here is a .zip file containing the .bib file and images necessary to compile. Here Matt provides the LaTeX code for a paper recently published in AJPS as well as some information on posters. |
| LaTeX code for first lab | This is just the LaTeX code for the Beamer presentation slides for the first lab. |