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Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures and results were compared. The latent class cluster analysis uncovered three classes representing differing levels of children's behavioral adjustment (well adjusted, average adjustment, functionally impaired), whereas the cluster analysis uncovered seven groups of child behavior. Results show a high degree of overlap, and each procedure offers unique information toward classifying child behavior.
DiStefano et al. (Wed,) studied this question.