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Title: Quality quandaries: Impact of only below limit of detection data

Journal Article · · Quality Engineering

Here, treating below limit of detection data as left-censored data rather than as passes can lead to large reductions in the number of tests needed to demonstrate a design requirement.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1325642
Report Number(s):
LA-UR-15-28965
Journal Information:
Quality Engineering, Vol. 28, Issue 3; ISSN 0898-2112
Publisher:
American Society for Quality ControlCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 1 work
Citation information provided by
Web of Science

References (6)

The use of Confidence or Fiducial Limits Illustrated in the case of the Binomial journal January 1934
Understanding the Metropolis-Hastings Algorithm journal November 1995
Understanding the Metropolis-Hastings Algorithm journal November 1995
The Advantages of Continuous Measurements over Pass/Fail Data journal December 2002
The BUGS project: Evolution, critique and future directions journal July 2009
Bayesian Data Analysis book July 2003

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