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Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models

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Random Effect and Latent Variable Model Selection

Part of the book series: Lecture Notes in Statistics ((LNS,volume 192))

Abstract

Mixed models are a powerful inferential tool with a wide range of applications including longitudinal studies, hierarchical modeling, and smoothing. Mixed models have become the state of the art for statistical information exchange and correlation modeling. Their popularity has been augmented by the availability of dedicated software, e.g., the Mixed procedure in SAS, the lme function in R and S², or the xtmixed f un c t i on i n STATA.

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Acknowledgments

Ciprian Crainiceanu's work was supported by NIH Grant AG025553-02 on the Effects of Aging on Sleep Architecture.

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Authors and Affiliations

  1. Department of Biostatistics, Johns Hopkins University, Baltimore, US

    Ciprian M. Crainiceanu

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  1. Ciprian M. Crainiceanu
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Correspondence to Ciprian M. Crainiceanu .

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Editors and Affiliations

  1. National Institute of Environmental Health Sciences Research Triangle Park, NC, USA

    David B. Dunson

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Crainiceanu, C.M. (2008). Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models. In: Dunson, D.B. (eds) Random Effect and Latent Variable Model Selection. Lecture Notes in Statistics, vol 192. Springer, New York, NY. https://doi.org/10.1007/978-0-387-76721-5_1

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