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Estimating the Number of Aberrant Laboratories*

Published online by Cambridge University Press:  27 July 2009

Ingram Olkin ,
Irwin Guttman  and
Robert Philips
Ingram Olkin
Affiliation:
Department of Statistics, Stanford University, Stanford, California 94305
Irwin Guttman
Affiliation:
Department of Statistics, University of Buffalo, Buffalo, NY 14214-3000
Robert Philips
Affiliation:
Department of Statistics, University of Toronto, Toronto, Ontario M5S 1A1, Canada
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Abstract

It has long been observed that independent laboratories differ in reporting the results of repeated experiments. The problem is to detect those laboratories that might be considered aberrant. Previous analyses have been based on an analysis of variance framework or on subset selection for the detection of aberrant laboratories. The present procedure is also based on an ANOVA model but uses a Bayesian estimate of the number of aberrant laboratories. Subsequent to the determination of the aberrant laboratories, a linear model is used to separate sampling and laboratory effects.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 9 , Issue 1 , January 1995 , pp. 133 - 150
Copyright
Copyright © Cambridge University Press 1995

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