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| || [wiki:/Session0 The week before the tutorial] || November 17 || Prepare || || [wiki:/Session1 Session 1] || November 24 || Linear and logistic regression || || [wiki:/Session2 Session 2] || November 25 || multilevel models || |
|| [[DenmarkMiniCourseSession0|The week before the tutorial]] || November 17 || Prepare || || [[DenmarkMiniCourseSession1|Session 1]] || November 24 || Linear and logistic regression || || [[DenmarkMiniCourseSession2|Session 2]] || November 25 || multilevel models || |
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| * Analyzing Linguistic Data: A Practical Introduction to Statistics using R by Harald Baayen (2008). [http://www.amazon.com/Analyzing-Linguistic-Data-Introduction-Statistics/dp/0521882591/ hardback ($97)] [http://www.amazon.com/Analyzing-Linguistic-Data-Introduction-Statistics/dp/0521709180/ paperback ($35)] '''[attachment:baayen_analyzing_08.pdf Complete electronic draft]'''. Baa08. | * Analyzing Linguistic Data: A Practical Introduction to Statistics using R by Harald Baayen (2008). [[http://www.amazon.com/Analyzing-Linguistic-Data-Introduction-Statistics/dp/0521882591/|hardback ($97)]] [[http://www.amazon.com/Analyzing-Linguistic-Data-Introduction-Statistics/dp/0521709180/|paperback ($35)]] '''[[attachment:baayen_analyzing_08.pdf|Complete electronic draft]]'''. Baa08. |
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| * [http://www.amazon.com/Analysis-Regression-Multilevel-Hierarchical-Models/dp/0521867061/ 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/Analysis-Regression-Multilevel-Hierarchical-Models/dp/0521867061/|Data Analysis Using Regression and Multilevel/Hierarchical Models]] by Gelman & Hill (2007). [[http://www.stat.columbia.edu/~gelman/arm/|Online resources]]. G&H07. |
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| * [http://www.amazon.com/Introductory-Statistics-R-Peter-Dalgaard/dp/0387954759/ Introductory Statistics with R] by Peter Dalgaard (2004). [http://staff.pubhealth.ku.dk/~pd/ISwR.html Online resources]. [http://site.ebrary.com/lib/rochester/Doc?id=10047812 Electronic copy through U of R libraries]. Dal04. * [http://www.amazon.com/Categorical-Analysis-Wiley-Probability-Statistics/dp/0471360937/ Categorical Data Analysis] by Alan Agresti (2002). [http://www.stat.ufl.edu/~aa/cda/cda.html Online resources]. Agr02. |
* [[http://www.amazon.com/Introductory-Statistics-R-Peter-Dalgaard/dp/0387954759/|Introductory Statistics with R]] by Peter Dalgaard (2004). [[http://staff.pubhealth.ku.dk/~pd/ISwR.html|Online resources]]. [[http://site.ebrary.com/lib/rochester/Doc?id=10047812|Electronic copy through U of R libraries]]. Dal04. * [[http://www.amazon.com/Categorical-Analysis-Wiley-Probability-Statistics/dp/0471360937/|Categorical Data Analysis]] by Alan Agresti (2002). [[http://www.stat.ufl.edu/~aa/cda/cda.html|Online resources]]. Agr02. |
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| * [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). |
* [[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). |
HLP Lab Mini Course on Regression Methods
November 24 & 25, Copenhagen, Denmark
Goal of this workshop
To provide sufficient background and a platform for a discussion of common issues in linear and logistic regression fitting, including applications of multilevel models.
Some of the specific questions that you have sent me:
- Data distributions and transformations to increase normality
- How robust are LME's in the face of normality violations (short answer: relatively robust; there are worse violations)
- Evaluation of multiple logistic regression model
- also: "Precision measures" -- I assume this refers to tests of the quality of fit of a model?
- decision criteria to include or exclude variables. Why researchers sometimes keep insignificant predictors in the model?
- When to use mixed-effects models
- Conceptual background
November 17 |
Prepare |
|
November 24 |
Linear and logistic regression |
|
November 25 |
multilevel models |
Readings
In the sessions, I refer to the following readings:
Obligatory:
Analyzing Linguistic Data: A Practical Introduction to Statistics using R by Harald Baayen (2008). hardback ($97) paperback ($35) Complete electronic draft. Baa08.
Recommended:
Data Analysis Using Regression and Multilevel/Hierarchical Models by Gelman & Hill (2007). Online resources. G&H07.
Also useful:
Introductory Statistics with R by Peter Dalgaard (2004). Online resources. Electronic copy through U of R libraries. Dal04.
Categorical Data Analysis by Alan Agresti (2002). Online resources. Agr02.
R packages
Please make sure you have the following R packages installed before you attend the workshop. Please also note that I will assume R version 2.7.1, and it's easier if you have that same version (or at least that recent a version).