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:: 2016-04-22

Research Org.:: Los Alamos National Lab. (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.

Copy to clipboard


                    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

Copy to clipboard


                    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.

Copy to clipboard


                    
@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         = {2016},

  month        = {4}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1080/08982112.2015.1133823

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 1 work

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

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
DOI: 10.1093/biomet/26.4.404

Understanding the Metropolis-Hastings Algorithm
journal, November 1995

Chib, Siddhartha; Greenberg, Edward
The American Statistician, Vol. 49, Issue 4
DOI: 10.1080/00031305.1995.10476177

Understanding the Metropolis-Hastings Algorithm
journal, November 1995

Chib, Siddhartha; Greenberg, Edward
The American Statistician, Vol. 49, Issue 4
DOI: 10.2307/2684568

The Advantages of Continuous Measurements over Pass/Fail Data
journal, December 2002

Hamada, Michael
Quality Engineering, Vol. 15, Issue 2
DOI: 10.1081/QEN-120015857

The BUGS project: Evolution, critique and future directions
journal, July 2009

Lunn, David; Spiegelhalter, David; Thomas, Andrew
Statistics in Medicine, Vol. 28, Issue 25
DOI: 10.1002/sim.3680

Similar Records in DOE PAGES and OSTI.GOV collections:

The Impact of Below Detection Limit Samples in (NPP) Decommissioning Residual Risk Assessment - 17033

Conference Kim, Jung Hwan ; Hornibrook, Carol ; Yim, Man-Sung

There are some technical problems with finalizing regulations and standards that address nuclear power plant (NPP) decommissioning site soil analyses for license termination. It is difficult to know how to best include detection limit observations from site soil analysis, because typical soil collection data is reported above, at, and below the detection limit. In addition, multiple detection limits are required to adequately estimate the soil radionuclide concentrations. In the literature, researchers analyzing environmental data refer to below the detection limit observations as 'left-censored data'. Left-censored data are less than the detection limit of the instrument(s) that made the measurements. Conventionalmore »« less
Analysis of toxic air contaminant data containing concentrations below the limit of detection

Journal Article Rao, S T ; Jia-Yeong, Ku ; Rao, K S - Journal of the Air and Waste Management Association; (United States)

Air quality data often contain several observations reported only as below the analytical limit of detection (LOD), resulting in censored data sets. Such censored and/or truncated data sets tend to complicate statistifcal analysis. This paper discusses various procedures for estimating mean concentration and its 95% confidence bounds from air contaminant data sets which contain values that are reported as below the LOD. A quantitative approach for assessing the uncertainty inherent in the estimated mean concentration due to (a) presence of values below the LOD in the data set, and (b) natural variability of atmospheric concentration data, is described. The utilitymore »« less
https://doi.org/10.1080/10473289.1991.10466856
Estimating mean and variance for environmental samples with below detection limit observations

Journal Article Newman, M C ; Dixon, P M ; Pinder, III, J E ; ... - Water Resources Bulletin; (United States)

Left-censoring of data sets complicates subsequent statistical analyses Generally, substitution or deletion methods provide poor estimates of the mean and variance of censored samples. These substitution and deletion methods include the use of values above the detection limit (DL) only, or substitution of 0, DL/2 or the DL for the below DL values during the calculation of mean and variance. A variety of statistical methods provides better estimators for different types of distributions and censoring. Maximum likelihood and order statistics methods compare favorably to the substitution or deletion methods. Selected statistical methods applicable to left-censoring of environmental data sets aremore »« less
https://doi.org/10.1111/j.1752-1688.1989.tb05406.x
Statistical analysis of water-quality data affected by limits of detection

Thesis/Dissertation Porter, P S

Many water-quality problems are related to substances present at concentrations too low to be measured precisely. Obtaining information from a monitoring system that produces many results near the fringes of analytic capabilities is not straightforward. This thesis discusses concerns one should have when statistically analyzing water-quality data from such a system. Two general approaches are discussed. The traditional approach is to regard all measurements as precise or imprecise. Precise results are simply numerical responses, for which statistical analysis may lead to valid and sound monitoring information. Imprecise results are reported as ND, or not detected, with criteria for reporting basedmore »« less
Effect of censoring trace-level water-quality data on trend-detection capability

Journal Article Gilliom, R J ; Hirsch, R M ; Gilroy, E J - Environ. Sci. Technol.; (United States)

Monte Carlo experiments were used to evaluate whether trace-level water-quality data that are routinely censored (not reported) contain valuable information for trend detection. Measurements are commonly censored if they fall below a level associated with some minimum acceptable level of reliability (detection limit). Trace-level organic data were simulated with best- and worst-case estimates of measurement uncertainty, various concentrations and degrees of linear trend, and different censoring rules. The resulting classes of data were subjected to a nonparametric statistical test for trend. For all classes of data evaluated, trends were most effectively detected in uncensored data as compared to censored datamore »« less
https://doi.org/10.1021/es00125a009

Similar Records

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

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