Abstract
This piece is meant to help you understand and master two-level linear modeling in an accessible, swift, and fun way (while being based on rigorous and up-to-date research). It is divided into four parts:
- PART 1 presents the three key principles of two-level linear modeling.
- PART 2 presents a three-step procedure for conducting two-level linear modeling using SPSS, Stata, R, or Mplus (from centering variables to interpreting the cross-level interactions).
- PART 3 presents the results from a series of simulations comparing the performances of SPSS, Stata, R, and Mplus.
- PART 4 gives a Q&A addressing multilevel modeling issues pertaining to statistical power, effect sizes, complex design, and nonlinear two-level regression.
The empirical example used in this tutorial is based on genuine data pertaining to ʼ90s and post-ʼ00s boy band member hotness and Instagram popularity. In reading this paper, you will have the opportunity to win a signed picture of Justin Timberlake.