Alternative Covariance Structures for Polynomial Models of Individual Growth and Change
Michigan State University
In studies of psychological change, researchers seek statistical models that are developmentally meaningful and provide a reasonable fit to the data. They also seek inferences that are fairly insensitive to questionable assumptions about the random behavior of their data. This chapter compares, contrasts, and integrates two modeling approaches in light of these concerns: a hierarchical linear model and a multivariate model for incomplete data. If the complete data are multivariate normal with homogeneous covariance structure, now-standard hierarchical models are submodels of the multivariate model. ...