• HLPMiniCourse

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.

==== 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