A structural equations modeling approach to the general linear mixed model

(from the chapter) This chapter presents a method based on a structural equation modeling (SEM) framework for estimating models representing specific instances of the general linear mixed model (GLMM; Laird and Ware, 1982). The authors state their choice of the GLMM as a starting point, firstly, because it can be considered the basis of the general multilevel modeling approach; and secondly, because the GLMM appears in a form that can be directly translated into the SEM framework. This correspondence allows one to estimate many different models, including repeated-measures analysis of variance, with patterned residual matrices as SEM. Comments by D. W. Osgood on this chapter and that by S Raudenbush (see record 2001-01077-002) follows Chapter 3 on pp. 97-104.