 Multilevel regression mixture analysisBengt Muthén and Tihomir Asparouhov Journal of the Royal Statistical Society Series A, 2009, vol. 172, issue 3, 639-657 Abstract: Summary. A two‐level regression mixture model is discussed and contrasted with the conventional two‐level regression model. Simulated and real data shed light on the modelling alternatives. The real data analyses investigate gender differences in mathematics achievement from the US National Education Longitudinal Survey. The two‐level regression mixture analyses show that unobserved heterogeneity should not be presupposed to exist only at level 2 at the expense of level 1. Both the simulated and the real data analyses show that level 1 heterogeneity in the form of latent classes can be mistaken for level 2 heterogeneity in the form of the random effects that are used in conventional two‐level regression analysis. Because of this, mixture models have an important role to play in multilevel regression analyses. Mixture models allow heterogeneity to be investigated more fully, more correctly attributing different portions of the heterogeneity to the different levels. Date: 2009 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:172:y:2009:i:3:p:639-657 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC. |
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