HLP Lab Mini Course on Regression Methods

May 27 2008 - June 9 2008

Texts

• [http://www.amazon.com/Analysis-Regression-Multilevel-Hierarchical-Models/dp/0521867061/ref=sr_1_1?ie=UTF8&s=books&qid=1211219851&sr=8-1 Data Analysis Using Regression and Multilevel/Hierarchical Models] by Gelman & Hill (2007). [http://www.stat.columbia.edu/~gelman/arm/ Online resources]. G&H07.

• [http://www.amazon.com/Analyzing-Linguistic-Data-Introduction-Statistics/dp/0521882591/ref=sr_1_1?ie=UTF8&s=books&qid=1211219948&sr=8-1 Analyzing Linguistic Data: A Practical Introduction to Statistics using R] by Harald Baayen (2008). [attachment:baayen_analyzing_08.pdf Complete electronic draft]. Baa08.

• [http://www.amazon.com/Introductory-Statistics-R-Peter-Dalgaard/dp/0387954759/ref=sr_1_1?ie=UTF8&s=books&qid=1211228905&sr=8-1 Introductory Statistics with R]. [http://staff.pubhealth.ku.dk/~pd/ISwR.html Online resources]. Dal04.

R packages

• [http://cran.r-project.org/web/packages/Design/index.html Design]. Linear and generalized linear regression.

• [http://cran.r-project.org/web/packages/lme4/index.html lme4]. Multilevel modeling.

• [http://cran.r-project.org/web/packages/arm/index.html ARM]. Companion package for Gelman & Hill (2007).

• [http://cran.r-project.org/web/packages/languageR/index.html languageR]. Companion package for Baayen (2008).

Week 0: Basics

Understanding of this material will be assumed throughout the course. Please read these introductory materials and make sure you understand them before beginning the readings for the first session.

1. Reading

Week 1: Linear regression

Session 1:

Session 2:

Week 2: Logistic regression

Session 3:

Session 4:

Week 3: Multilevel regression

Session 5:

Session 6:

Week 4: Implementations (optional)

Session 7: lme4 implementation details