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== Texts == * [http://www.amazon.com/Applied-Regression-Analysis-Generalized-Linear/dp/0761930426/ref=sr_1_3/002-3707949-0352833?ie=UTF8&s=books&qid=1211219661&sr=8-3 Applied Regression Analysis and Generalized Linear Models] by John Fox. [http://socserv.mcmaster.ca/jfox/Books/Applied-Regression-2E/index.html Online resources]. * [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. [http://www.stat.columbia.edu/~gelman/arm/ Online resources]. * [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. |
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| || Reading || attachment:implementation.pdf attachment:computation.pdf|| | || Reading || attachment:Implementation.pdf attachment:Theory.pdf attachment:Notes.pdf|| |
HLP Lab Mini Course on Regression Methods
May 27 2008 - June 9 2008
Texts
[http://www.amazon.com/Applied-Regression-Analysis-Generalized-Linear/dp/0761930426/ref=sr_1_3/002-3707949-0352833?ie=UTF8&s=books&qid=1211219661&sr=8-3 Applied Regression Analysis and Generalized Linear Models] by John Fox. [http://socserv.mcmaster.ca/jfox/Books/Applied-Regression-2E/index.html Online resources].
[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. [http://www.stat.columbia.edu/~gelman/arm/ Online resources].
[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.
Week 1: Linear regression
1. Session 1:
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2. Session 2:
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Week 2: Logistic regression
1. Session 3:
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2. Session 4:
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Week 3: Multilevel regression
1. Session 5:
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2. Session 6:
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Week 4: Implementations (optional)
1. Session 7: lme4 implementation details
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attachment:Implementation.pdf attachment:Theory.pdf attachment:Notes.pdf |
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