Detection of analytical bias
Literature Information
Publication Date
2003-07-21
DOI
10.1039/B212547A
Impact Factor
4.616
Authors
Márcio V. de Castilho, Heleno Bolfarine, Mário de Castro
View Original
Abstract
The main object of this paper is to consider maximum likelihood estimators for models used in detection of analytical bias. We consider the regression model proposed in Ripley and Thompson (Analyst, 112, 1987, p. 377) with an EM-type algorithm for computing maximum likelihood estimators and obtain consistent estimators for the asymptotic variance of the maximum likelihood estimators, which seems not to be available in the literature. Wald type statistics are proposed for testing hypothesis related to the bias of the analytical methods with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels. The main conclusion is that proposed approaches in the literature underestimate the covariance matrix of the maximum likelihood estimators. Results of simulation studies and applications to real data sets are reported to illustrate comparisons with other approaches.
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Source Journal
Analyst
CiteScore:
7.8
Self-citation Rate:
5.6%
Articles per Year:
653
Analyst publishes analytical and bioanalytical research that reports premier fundamental discoveries and inventions, and the applications of those discoveries, unconfined by traditional discipline barriers.
Recommended Compounds
3-(3-Ethyl-1-methyl-3-azepanyl)phenol hydrochloride (1:1)
CAS Number:
59263-76-2
Molecular Formula:
C15H24ClNO
![[4-Amino-2-(methylsulfanyl)-5-pyrimidinyl]methanol structure](https://static.chemtradehub.com/structs/588/588-36-3-fc73.webp "[4-Amino-2-(methylsulfanyl)-5-pyrimidinyl]methanol structure")
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