Multilevel Modeling: What it is, when you need it (and when you don't), and 4 important questions to ask every time you use it
Information Session | September 5 | 12:10-1:15 p.m. | 1104 Berkeley Way West
Amie Gordon, Postdoctoral Fellow, UC San Francisco
Multilevel modeling (MLM) is everywhere these days. Reviewers are increasingly asking people to use this advanced approach to statistics and there are more and more online calculators devoted to helping people run MLM analyses. But MLM requires making a lot of choices, and without a clear understanding of what MLM is, it is easy to make mistakes. In this one hour whirlwind tour of MLM, I will introduce you to the topic, help you figure out when MLM is needed (and when it is not), and describe the 4 questions you should ask yourself every time you use it: (1) What is the structure of my data? (2) Are my effects fixed or random? (3) What type of centering should I use? (4) Which covariance matrices should I use?