An Evaluation of Aggregated and Disaggregated Approaches to Multilevel Factor Scoring

Abstract

Approaches to multilevel measurement modeling are often distinguished as aggregated or disaggregated. While past research has established the benefits and limitations of these modeling frameworks, none have critically evaluated the reliability of factor score predictions representing level-1 and level-2 processes. We utilize simulation methodology to explore factor-scoring techniques within both modeling frameworks. Results suggest that factor scores from the aggregated approach are at least as reliable as those from the disaggregated approach after simple numeric transformations, contingent on accurate knowledge of the level-2 factor structure in the presence of cross-level configural non-invariance. Further, given differences in the range of reliability across approaches when fewer clusters are available for analysis, the aggregated approach may be preferable within any given sample.