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Effect of censoring trace-level water-quality data on trend-detection capability

Environmental Science and Technology

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Abstract

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 data even when the data censored were highly unreliable. Thus, censoring data at any concentration level may eliminate valuable information. Whether or not valuable information for trend analysis is, in fact, eliminated by censoring of actual rather than simulated data depends on whether the analytical process is in statistical control and bias is predictable for a particular type of chemical analyses.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Effect of censoring trace-level water-quality data on trend-detection capability
Series title:
Environmental Science and Technology
Volume
18
Issue:
7
Year Published:
1984
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Environmental Science and Technology
First page:
530
Last page:
535
Number of Pages:
6