The ‘softer kind’ of tutorial on linear mixed effect regression

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I recently was pointed to this nice and very accessible tutorial on linear mixed effects regression and how to run them in R by Bodo Winter (at UC Merced). If you don’t have much or any background in this type of model, I recommend you pair it with a good conceptual introduction to these models like Gelman and Hill 2007 and perhaps some slides from our LSA 2013 tutorial.

There are a few thing I’d like to add to Bodo’s suggestions regarding how to report your results:

  1. be clear how you coded the variables since this does change the interpretation of the coefficients (the betas that are often reported). E.g. say whether you sum- or treatment-coded your factors, whether you centered or standardized continuous predictors etc. As part of this, also be clear about the direction of the coding. For example, state that you “sum-coded gender as female (1) vs. male (-1)”. Alternatively, report your results in a way that clearly states the directionality (e.g., “Gender=male, beta = XXX”).
  2. please also report whether collinearity was an issue. E.g., report the highest fixed effect correlations.

Happy reading.

 

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