Quality quandaries: Impact of only below limit of detection data

Hamada, Michael Scott; Weaver, Brian Phillip; Schmidt, Chad Christopher

doi:10.1080/08982112.2015.1133823

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

Abstract

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.

Authors:

Hamada, Michael Scott ^[1]; Weaver, Brian Phillip ^[1]; Schmidt, Chad Christopher ^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:: Fri Apr 22 00:00:00 EDT 2016

Research Org.:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1325642

Report Number(s):: LA-UR-15-28965
Journal ID: ISSN 0898-2112

Grant/Contract Number:: AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: Quality Engineering

Additional Journal Information:: Journal Volume: 28; Journal Issue: 3; Journal ID: ISSN 0898-2112

Publisher:: American Society for Quality Control

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Hamada, Michael Scott, Weaver, Brian Phillip, and Schmidt, Chad Christopher. Quality quandaries: Impact of only below limit of detection data.  United States: N. p., 2016. 
Web.  doi:10.1080/08982112.2015.1133823.

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                    Hamada, Michael Scott, Weaver, Brian Phillip, & Schmidt, Chad Christopher. Quality quandaries: Impact of only below limit of detection data.  United States.  https://doi.org/10.1080/08982112.2015.1133823

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                    Hamada, Michael Scott, Weaver, Brian Phillip, and Schmidt, Chad Christopher. Fri .  
"Quality quandaries: Impact of only below limit of detection data".  United States.  https://doi.org/10.1080/08982112.2015.1133823.  https://www.osti.gov/servlets/purl/1325642.

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@article{osti_1325642,

  title        = {Quality quandaries: Impact of only below limit of detection data},

  author       = {Hamada, Michael Scott and Weaver, Brian Phillip and Schmidt, Chad Christopher},

  abstractNote = {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.},

  doi          = {10.1080/08982112.2015.1133823},

  journal      = {Quality Engineering},

  number       = 3,

  volume       = 28,

  place        = {United States},

  year         = {Fri Apr 22 00:00:00 EDT 2016},

  month        = {Fri Apr 22 00:00:00 EDT 2016}

}

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https://doi.org/10.1080/08982112.2015.1133823

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Works referenced in this record:

The use of Confidence or Fiducial Limits Illustrated in the case of the Binomial
journal, January 1934

Clopper, C. J.; Pearson, E. S.
Biometrika, Vol. 26, Issue 4
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The Advantages of Continuous Measurements over Pass/Fail Data
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Hamada, Michael
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The BUGS project: Evolution, critique and future directions
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Lunn, David; Spiegelhalter, David; Thomas, Andrew
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Bayesian Data Analysis
book, July 2003

Gelman, Andrew; Carlin, John B.; Stern, Hal S.
Chapman and Hall/CRC
DOI: 10.1201/9780429258480

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

Abstract

Citation Formats

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

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