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Linear Mixed-Effects and Generalized Linear Models in R

This two-day workshop will focus on linear mixed-effects and generalized linear models (GLMs) using the R programming language. We will begin with a refresher on interpreting linear regression under various data transformations and then move on to linear mixed-effects models and GLMs. More advanced topics will include standardizing predictors, group-level predictors, variance and correlation structures, and overdispersed GLMs. We will concentrate on practical elements such as choosing a modeling approach, the process of building and understanding a model, model checking, and plotting and interpreting model output.


By the end of the two-day workshop, you will be able to develop models using your own data and troubleshoot the main problems that arise in the process. You will also become familiar with two R packages for model fitting (lme4 and nlme) and R packages to help manipulate and plot your data and models (e.g. dplyr, ggplot2, broom).


Prior to taking this workshop, you should be reasonably comfortable with R and linear regression. Some background with dplyr and ggplot2 would be helpful, but participants can also complete some short tutorials before arriving to learn these packages.

* Please note that you will need to bring your own laptop with the appropriate software loaded. Closer to the workshop date, you will receive an email with final details/instructions.


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