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Random effects model for bias estimation: higher‐order asymptotic inference
Author(s) -
Rukhin Andrew L.
Publication year - 2015
Publication title -
stat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 18
ISSN - 2049-1573
DOI - 10.1002/sta4.82
Subject(s) - reliability (semiconductor) , statistical inference , inference , statistics , confidence interval , coverage probability , computer science , certification , frequentist inference , mathematics , certificate , econometrics , algorithm , artificial intelligence , bayesian inference , bayesian probability , political science , power (physics) , physics , quantum mechanics , law
A common issue in physical, chemical and biometrical applications is to validate a laboratory's method. For that purpose, a lab performs measurements on a certified reference material with a given coverage interval. These reference materials are a major tool for assuring quality and reliability of results obtained by a lab in analysis and testing. Assuming that the measurand is random with a normal distribution whose parameters are obtained from the reference material certificate, new remarkably accurate confidence intervals for the bias are derived. These procedures are based on modern higher‐order asymptotic statistical methods. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.