- A test for cluster bias: Detecting violations of measurement invariance across clusters in multilevel data
- Structural Equation Modeling
- Volume | Issue number
- 20 | 2
- Pages (from-to)
- Document type
- Faculty of Social and Behavioural Sciences (FMG)
- Research Institute of Child Development and Education (RICDE)
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.
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