Abstract
Multilevel regression models: Applications in school psychology. Data collection procedures in the behavioral sciences do not always follow the rules of simple random sampling, an assumption of ordinary least squares regression. This is the case in cluster sampling designs which contain more than one type of experimental unit, such as subjects that are nested within classes, schools or companies. Failure of taking into consideration the special structure of the data results in estimation bias for the standard error and in an increase in the probability of inference errors. Multilevel analysis models this relationship among the observations while pr oviding unbiased standard error and estimates of the contextual variability of regression coefficients. The purpose of this paper is to simplify multilevel analysis as a generalization of the analysis of covariance on the basis of commonly used statistical concepts such as repeated measures designs, fixed and random effects models. Several application examples in school psychology are reviewed.
