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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Ed. by Gillery, Philippe / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Schlattmann, Peter / Tate, Jillian R. / Tsongalis, Gregory J.

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Mean and variance quality control for multiple correlated levels of replicated control samples

John H. Livesey1

1.

Corresponding author: John H. Livesey, Endolab, Christchurch Hospital, Private Bag 4710, Christchurch, New Zealand Fax: +64-3-3640818,

Citation Information: Clinical Chemical Laboratory Medicine. Volume 43, Issue 11, Pages 1240–1252, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: 10.1515/CCLM.2005.215, November 2005

Publication History

Received:
April 14, 2005
Accepted:
August 18, 2005

Abstract

Mean and variance rules for quality control are more powerful than rules based on individual values. An algorithm for applying such rules is described that controls type I errors (false alarms), while allowing for multiple levels of quality control samples, correlation between levels, small numbers of preliminary values, replication of samples and autocorrelation arising from random effects. Based on ANOVA and empirical approximations for small samples, the algorithm maintains a low per-batch probability of type I errors. Three statistics are computed, zm, zb and zw, which are shown by simulations to be primarily sensitive to a concordant shift in the quality control values, a discordant shift in the values, and an increase in random variability, respectively. Simulations also show that for a Gaussian distribution of analytical errors, the per-batch probability of a type I error is likely to be within the range 0.0045–0.0071 for two to four levels where there are 20–100 preliminary batches and the inter-level correlations are between zero and 0.8. This partial separation of out-of-control alarms into three components provides more assistance with trouble-shooting than do multivariate quality control schemes based on Hotelling's T2, while retaining comparable power.

Keywords: biometry; clinical chemistry; laboratory techniques and procedures; quality control

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[1]
John H. Livesey
Clinical Biochemistry, 2007, Volume 40, Number 13-14, Page 1032

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