ABSTRACT
In the previous chapter the multilevel modeling approach to analysis of nested data was introduced, along with relevant notation and definitions of random intercepts and coefficients. We will now devote Chapter 3 to introducing the lme4 package for fitting multilevel models in R. In Chapter 1 we provided an overview of the R lm() function for fitting linear regression models. As will become apparent, the syntax used in the estimation of multilevel models in R is very similar to that of single-level linear models. After providing a brief discussion of the lme4 package for fitting multilevel models for continuous data, we will devote the remainder of the chapter to extended examples applying the principles that we introduced in Chapter 2, using R.
