Statistical modeling helps to compress the raw data we have into a simple mathematical formula that we can use for understanding the relationship between two or more variables, or in some situation, use to predict data from new input.
Simple linear model could easily help to model the relationship between two directly correlated variables, but in most cases, the world is too complicated to simple linear model. In this case, linear mixed model comes into play. Incorporating both fixed effects and random effects, this modeling technique attempt to prevent a false negative correlation between the variables, or mis interpretation of the trends.
This video is attempting to summarize the concept of modeling and how you can run LMM in R.
Scripts
https://github.com/brandonyph/Basics-Linear-Mixed-Model
Slides
https://docs.google.com/presentation/d/1koQM0SNB1AS2LGwRpHg1kqiHRIIfJyYjD7G-meUm8kc/edit
Original tutorial
https://bodowinter.com/tutorial/bw_LME_tutorial2.pdf
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