Abstract
We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings are equal to the between-level factor loadings, and whether the between-level residual variances are zero. The test is illustrated with an example from school research. In a simulation study, we show that the cluster bias test has sufficient power, and the proportions of false positives are close to the chosen levels of significance.
Original language | English |
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Pages (from-to) | 265-282 |
Number of pages | 18 |
Journal | Structural Equation Modeling |
Volume | 20 |
DOIs | |
Publication status | Published - 2013 |
Keywords
- cluster bias
- measurement bias
- multilevel structural equation modeling