Comparison of designs for the three-fold nested random model

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초록

The quality of estimation of variance components depends on the design used as well as on the unknown values of the variance components. In this article, three designs are compared, namely, the balanced, staggered, and inverted nested designs for the three-fold nested random model. The comparison is based on the so-called quantile dispersion graphs using analysis of variance (ANOVA) and maximum likelihood (ML) estimates of the variance components. It is demonstrated that the staggered nested design gives more stable estimates of the variance component for the highest nesting factor than the balanced design. The reverse, however, is true in case of lower nested factors. A comparison between ANOVA and ML estimation of the variance components is also made using each of the aforementioned designs.

키워드

ANOVAbalanced nested designfour-stage nested experimentinverted nested designmaximum likelihoodquantile dispersion graphsstaggered nested designvariance componentsVARIANCE-COMPONENTS ESTIMATIONQUANTILE DISPERSION GRAPHSSAMPLING DISTRIBUTIONSSTANDARD DEVIATIONSSPATIAL SCALE
제목
Comparison of designs for the three-fold nested random model
저자
Jung, Byoung CheolKhuri, Andre I.Lee, Juneyoung
DOI
10.1080/02664760801924079
발행일
2008
유형
Article
저널명
Journal of Applied Statistics
35
6
페이지
701 ~ 715