Diagnostics for mixed – model analysis of variance

Richard J. Beckman; Christopher J. Nachtsheim; R. Dennis Cook

doi:10.1080/00401706.1987.10488269

Diagnostics for mixed – model analysis of variance

Richard J. Beckman, Christopher J. Nachtsheim, R. Dennis Cook

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Abstract

We describe a new method for assessment of model inadequacy in maximum-likelihood mixed-model analysis of variance. In particular, we discuss its use in diagnosing perturbations from the usual assumption of constant error variance and from the assumption that each realization of a given random factor has been drawn from the same normal population. Computer implementation of the procedure is described, and an example is presented, involving the analysis of filter cartridges used with commercial respirators.

Original language	English (US)
Pages (from-to)	413-426
Number of pages	14
Journal	Technometrics
Volume	29
Issue number	4
DOIs	https://doi.org/10.1080/00401706.1987.10488269
State	Published - Nov 1987

Bibliographical note

Funding Information:
This work was supported in part by National Science Foundation Grant DMS-860 1314 and by Nuclear Regulatory Commission Grant RES 60-83-176. We would like to thank Mark Johnson and Luis Escobar for their comments on an earlier draft of this article. We also thank A. Juan.

Keywords

Curvature
Likelihood displacement
Local influence
Random effects

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abstract = "We describe a new method for assessment of model inadequacy in maximum-likelihood mixed-model analysis of variance. In particular, we discuss its use in diagnosing perturbations from the usual assumption of constant error variance and from the assumption that each realization of a given random factor has been drawn from the same normal population. Computer implementation of the procedure is described, and an example is presented, involving the analysis of filter cartridges used with commercial respirators.",

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note = "Funding Information: This work was supported in part by National Science Foundation Grant DMS-860 1314 and by Nuclear Regulatory Commission Grant RES 60-83-176. We would like to thank Mark Johnson and Luis Escobar for their comments on an earlier draft of this article. We also thank A. Juan.",

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T1 - Diagnostics for mixed – model analysis of variance

AU - Beckman, Richard J.

AU - Nachtsheim, Christopher J.

AU - Cook, R. Dennis

N1 - Funding Information: This work was supported in part by National Science Foundation Grant DMS-860 1314 and by Nuclear Regulatory Commission Grant RES 60-83-176. We would like to thank Mark Johnson and Luis Escobar for their comments on an earlier draft of this article. We also thank A. Juan.

PY - 1987/11

Y1 - 1987/11

N2 - We describe a new method for assessment of model inadequacy in maximum-likelihood mixed-model analysis of variance. In particular, we discuss its use in diagnosing perturbations from the usual assumption of constant error variance and from the assumption that each realization of a given random factor has been drawn from the same normal population. Computer implementation of the procedure is described, and an example is presented, involving the analysis of filter cartridges used with commercial respirators.

AB - We describe a new method for assessment of model inadequacy in maximum-likelihood mixed-model analysis of variance. In particular, we discuss its use in diagnosing perturbations from the usual assumption of constant error variance and from the assumption that each realization of a given random factor has been drawn from the same normal population. Computer implementation of the procedure is described, and an example is presented, involving the analysis of filter cartridges used with commercial respirators.

KW - Curvature

KW - Likelihood displacement

KW - Local influence

KW - Random effects

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VL - 29

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EP - 426

JO - Technometrics

JF - Technometrics

IS - 4

ER -

Diagnostics for mixed – model analysis of variance

Abstract

Bibliographical note

Keywords

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