Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Structural Equation Modeling on 28/08/2015, available online: http://wwww.tandfonline.com 10.1080/10705511.2015.1035437
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Using multilevel regression mixture models to identify level-1 heterogeneity in level-2 effects
AU - Van Horn, M. Lee
AU - Feng, Y.
AU - Kim, Minjung
AU - Lamont, Andrea E.
AU - Feaster, Daniel
AU - Jaki, Thomas
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Structural Equation Modeling on 28/08/2015, available online: http://wwww.tandfonline.com 10.1080/10705511.2015.1035437
PY - 2016
Y1 - 2016
N2 - This article 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 1 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 0. 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 that can be answered with this method and the issues faced when estimating multilevel regression mixtures.
AB - This article 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 1 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 0. 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 that can be answered with this method and the issues faced when estimating multilevel regression mixtures.
KW - heterogeneity in contextual effects
KW - multilevel regression mixtures
KW - regression mixture modeling
U2 - 10.1080/10705511.2015.1035437
DO - 10.1080/10705511.2015.1035437
M3 - Journal article
VL - 23
SP - 259
EP - 269
JO - Structural Equation Modeling
JF - Structural Equation Modeling
SN - 1070-5511
IS - 2
ER -