ANALYZING CENSORED WATER QUALITY DATA USING A NON-PARAMETRIC APPROACH
In the analysis of water quality data, samples with concentrations reported below the limit of detection (LOD) are referred to as Type I censored on the left. A variety of procedures have been proposed for estimating descriptive statistics from left-censored data. Usually, the estimation is carried...
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Veröffentlicht in: | Journal of the American Water Resources Association 1997-06, Vol.33 (3), p.615-624 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In the analysis of water quality data, samples with concentrations reported below the limit of detection (LOD) are referred to as Type I censored on the left. A variety of procedures have been proposed for estimating descriptive statistics from left-censored data. Usually, the estimation is carried out by either replacing the LOD with a constant between 0 and the LOD, or assuming the data follow a normal or lognormal distribution. In this paper, a simple transformation is proposed to convert multiple left-censored water quality data to right-censored data. The transformed cumulative distribution is similar to a survival function, and enables use of survival analysis techniques for left-censored data. In particular, the product limit method (Kaplan-Meier estimator) is applied to estimate descriptive statistics from the transformed data. The performance of the Kaplan-Meier estimator is compared with maximum likelihood, probability plotting, and substitution methods by Monte Carlo simulations. The Kaplan-Meier estimator performs as well as or better than these more familiar methods. Finally, the Kaplan-Meier estimator is used to analyze some priority pollutant data collected in sediment from the central basin of Puget Sound. |
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ISSN: | 1093-474X 1752-1688 |
DOI: | 10.1111/j.1752-1688.1997.tb03536.x |