Mini-tutorial on regression and mixed (linear & logit) models in R

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This summer, Austin Frank and I organized a six 3h-session tutorial on regression and mixed models. It is posted on our HLP lab wiki and consists out of reading suggestions and commented R scripts that we went through in class. Among the topics (also listed for each session on the wiki) are:

  • linear & logistics regression
  • linear & logit mixed/multilevel/hierarchical models
  • model evaluation (residuals, outliers, distributions)
  • collinearity tests and dealing with collinearity
  • coding of variables (contrasts)
  • visualization

We used both Baayen’s 2008 textbook Analyzing Linguistic Data: A Practical Introduction to Statistics using R (available online) and Gelman and Hill’s 2007 book on Data Analysis using Regression and Multilevel/Hierarchical Models, both of which we can recommend (they also complement each other nicely). If you have questions about this class or you have suggestions for improvement, please send us an email or leave a comment to this page (we’ll get notified).


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