Multilevel Models From a Multiple Group Structural Equation Perspective
Whenever a promising new approach to data analysis becomes available many researchers are keen to try it out. In this chapter, we describe some of our attempts to use the new statistical models termed random coefficient or hierarchical or multilevel structural models (after Mason, Wong, Se Entwisle, 1984). Of course, multilevel models are not really new models because they have been available for over two decades (e.g., Aitkin 8c Longford, 1986; Hartley 8c Rao, 1967; Harville, 1977; Jennrich 8c Sampson, 1976; Lindley 8c Smith, 1972; Novick, Jackson, Thayer, 8c Cole, 1972). However, several recent reviews show a surge of interest in multilevel models (see Bock, 1989; Bryk 8c Raudenbush, 1993; Goldstein, 1987; Hoc & Kreft, 1994; Long ford, 1993; Muthen 8c Satorra, 1989; Raudenbush, 1988). These statistical models have become popular for a very good reason-multilevel models seem to provide a reasonable way to deal with the complex statistical and mathematical problems of “nested” or “clustered” data collection designs.