ABSTRACT
The multilevel regression model assumes that there is a hierarchical data set, often individuals within groups, with one single outcome or response variable measured at the lowest (individual) level, and explanatory variables at all levels. It is useful to view the multilevel regression model as a hierarchical system of regression equations. The outcome is predicted by level-1 predictors. Level-2 predictors predict the regression coefficients of the level-1 equation. This chapter explains the multilevel regression model for two- and three-level data, providing both the equations and an example. It ends with explaining notation and software.
