This paper proposes a novel exploratory approach for assessing how the effects of level-2 predictors differ across level-1 units. Multilevel regression mixture models are used to identify latent classes at level-1 that differ in the effect of one or more level-2 predictors. Monte Carlo simulations are used to demonstrate the approach with different sample sizes and to demonstrate the consequences of constraining 1 of the random effects to zero. An application of the method to evaluate heterogeneity in the effects of classroom practices on students is used to show the types of research questions which can be answered with this method and the issues faced when estimating multilevel regression mixtures.
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2015.
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