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  3. Hierarchical and Mixed Effects Models in R

Exercise

Building models

In this exercise, you will build a simple linear model (lm()) and then build a linear mixed-effects model (lmer()). The purpose of the first step is to make sure the data works well with a simple model because lm() outputs are easier to debug than lmer() outputs. During the next exercise, you will compare two different methods of statistical inference on the model.

Instructions 1/2

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  • Build a linear model using lm(). The goal of this step is to simply make sure the model builds without errors or warnings.
  • Have extra predicted by fixed-effects group (1st) and ID (2nd) from the sleep data.