Quantile dispersion graphs for the comparison of designs for a random two-way model

Juneyoung Lee; André I. Khuri

doi:10.1016/s0378-3758(00)00135-x

Quantile dispersion graphs for the comparison of designs for a random two-way model

Juneyoung Lee, André I. Khuri

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

The choice of optimal designs for the estimation of variance components depends on the method of estimation, the model used, and the values of the variance components themselves. Traditional comparisons of such designs cannot therefore be made without some prior knowledge of the variance components. This problem was circumvented by the introduction of the so-called quantile dispersion graphs (QDGs) in Khuri (1997) and Lee and Khuri (1999). The present article provides an extension of the use of the QDGs to the comparison of designs for an unbalanced random two-way model without interaction. Two methods of estimation of the variance components are considered, namely, the analysis of variance (ANOVA) and maximum likelihood (ML).

Original language	English
Pages (from-to)	123-137
Number of pages	15
Journal	Journal of Statistical Planning and Inference
Volume	91
Issue number	1
DOIs	https://doi.org/10.1016/s0378-3758(00)00135-x
Publication status	Published - 2000 Nov 1
Externally published	Yes

Bibliographical note

Funding Information:
The first author would like to acknowledge partial support of this research by the BK-21 project from the Korea Research Foundation.

Keywords

ANOVA estimation
Davies' algorithm
Maximum likelihood estimation
Primary 62J10
Secondary 62K99
Unbalanced design
Variance components

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1016/s0378-3758(00)00135-x

Cite this

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abstract = "The choice of optimal designs for the estimation of variance components depends on the method of estimation, the model used, and the values of the variance components themselves. Traditional comparisons of such designs cannot therefore be made without some prior knowledge of the variance components. This problem was circumvented by the introduction of the so-called quantile dispersion graphs (QDGs) in Khuri (1997) and Lee and Khuri (1999). The present article provides an extension of the use of the QDGs to the comparison of designs for an unbalanced random two-way model without interaction. Two methods of estimation of the variance components are considered, namely, the analysis of variance (ANOVA) and maximum likelihood (ML).",

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T1 - Quantile dispersion graphs for the comparison of designs for a random two-way model

AU - Lee, Juneyoung

AU - Khuri, André I.

N1 - Funding Information: The first author would like to acknowledge partial support of this research by the BK-21 project from the Korea Research Foundation.

PY - 2000/11/1

Y1 - 2000/11/1

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AB - The choice of optimal designs for the estimation of variance components depends on the method of estimation, the model used, and the values of the variance components themselves. Traditional comparisons of such designs cannot therefore be made without some prior knowledge of the variance components. This problem was circumvented by the introduction of the so-called quantile dispersion graphs (QDGs) in Khuri (1997) and Lee and Khuri (1999). The present article provides an extension of the use of the QDGs to the comparison of designs for an unbalanced random two-way model without interaction. Two methods of estimation of the variance components are considered, namely, the analysis of variance (ANOVA) and maximum likelihood (ML).

KW - ANOVA estimation

KW - Davies' algorithm

KW - Maximum likelihood estimation

KW - Primary 62J10

KW - Secondary 62K99

KW - Unbalanced design

KW - Variance components

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Quantile dispersion graphs for the comparison of designs for a random two-way model

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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