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Investigating the Incidence of type i errors for chronic whole effluent toxicity testing using Ceriodaphnia dubia
Author(s) -
Moore Timothy F.,
Canton Steven P.,
Grimes Max
Publication year - 2000
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620190114
Subject(s) - ceriodaphnia dubia , type i and type ii errors , toxicology , effluent , confidence interval , toxicity , statistics , false positive paradox , environmental science , mathematics , biology , environmental engineering , medicine , acute toxicity
The risk of Type I error (false positives) is thought to be controlled directly by the selection of a critical p value for conducting statistical analyses. The critical value for whole effluent toxicity (WET) tests is routinely set to 0.05, thereby establishing a 95% confidence level about the statistical inferences. In order to estimate the incidence of Type I errors in chronic WET testing, a method blank‐type study was performed. A number of municipal wastewater dischargers contracted 16 laboratories to conduct chronic WET tests using the standard test organism Ceriodaphnia dubia. Unbeknownst to the laboratories, the samples they received from the wastewater dischargers were comprised only of moderately hard water, using the U.S. Environmental Protection Agency's standard dilution water formula. Because there was functionally no difference between the sample water and the laboratory control/dilution water, the test results were expected to be less than or equal to 1 TUc (toxic unit). Of the 16 tests completed by the biomonitoring laboratories, two did not meet control performance criteria. Six of the remaining 14 valid tests (43%) indicated toxicity (TUc > 1) in the sample (i.e., no‐observed‐effect concentration or IC25 < 100%). This incidence of false positives was six times higher than expected when the critical value was set to 0.05. No plausible causes for this discrepancy were found. Various alternatives for reducing the rate of Type I errors are recommended, including greater reliance on survival endpoints and use of additional test acceptance criteria.