Efficient Analysis of Mixed Hierarchical and Cross-Classified Random Structures Using a Multilevel Model

Jon Rasbash and Harvey Goldstein

Journal of Educational and Behavioral Statistics, 1994, vol. 19, issue 4, 337-350

Abstract: An efficient and straightforward procedure is described for specifying and estimating parameters of general mixed models which contain both hierarchical and crossed random factors. This is done using a model formulated for purely hierarchically structured data and generalizes the results of Raudenbush (1993) . The exposition is for the continuous response linear model with natural extensions to generalized linear, nonlinear, and multivariate models.

Keywords: generalizability models; hierarchical data; iterative generalized least squares; mixed model; multilevel model; random cross-classification; variance components (search for similar items in EconPapers)
Date: 1994
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:19:y:1994:i:4:p:337-350

DOI: 10.3102/10769986019004337

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