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- W2012108610 abstract "Both structural equation models and hierarchical linear models (HLMs) have been commonly used in multilevel analysis. This study utilized simulated data to investigate the power difference among 3 multilevel models: HLM, deviation structural equation models, and a hybrid approach of HLM and structural equation models. Two factors were examined: sample size and the second-level regression coefficient, each of which was varied independently to evaluate the empirical power of the 3 models. Results showed that large samples were crucial for HLM to perform well. The power of the other 2 methods was similar and generally higher than HLM, although the deviation structural equation model had the best overall performance. In addition, power did not always increase with larger second-level regression coefficient values. First-level unit size was an important component with an asymptotic efficiency at about n = 35. HLM power was more susceptible to change in second-level regression coefficient values than the other 2 methods." @default.
- W2012108610 created "2016-06-24" @default.
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- W2012108610 date "2006-12-01" @default.
- W2012108610 modified "2023-10-13" @default.
- W2012108610 title "Comparing Empirical Power of Multilevel Structural Equation Models and Hierarchical Linear Models: Understanding Cross-Level Interactions" @default.
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- W2012108610 doi "https://doi.org/10.1207/s15328007sem1304_6" @default.
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