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Cited by 445

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Likelihood Ratio Tests in Linear Mixed Models with One Variance Component

Crainiceanu, Ciprian M., Ruppert, David·2004·Journal of the Royal Statistical Society Series B: Statistical Methodology

Abstract

Summary: We consider the problem of testing null hypotheses that include restrictions on the variance component in a linear mixed model with one variance component and we derive the finite sample and asymptotic distribution of the likelihood ratio test and the restricted likelihood ratio test. The spectral representations of the likelihood ratio test and the restricted likelihood ratio test statistics are used as the basis of efficient simulation algorithms of their null distributions. The large sample χ2 mixture approximations using the usual asymptotic theory for a null hypothesis on the boundary of the parameter space have been shown to be poor in simulation studies. Our asymptotic calculations explain these empirical results. The theory of Self and Liang applies only to linear mixed models for which the data vector can be partitioned into a large number of independent and identically distributed subvectors. One-way analysis of variance and penalized splines models illustrate the results.

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Metadata

Authors
Crainiceanu, C. M., & Ruppert, D.
Venue
Journal of the Royal Statistical Society Series B: Statistical Methodology
Published
2003-12-22
Volume
66
Issue
1
Pages
165-185
ISSN
  • 1369-7412 (ISSN-L)
  • 1467-9868
OpenAlex
W2051138734
Cited by
445
References
3
FWCI
10.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Likelihood Ratio Tests in Linear Mixed Models with One Variance Component. https://app.cochat.ai/papers/10.1111/j.1467-9868.2004.00438.x
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Crainiceanu, C. M., & Ruppert, D. (2004). Likelihood Ratio Tests in Linear Mixed Models with One Variance Component. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/j.1467-9868.2004.00438.x

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