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A statistical procedure for modeling continuous toxicity data
Author(s) -
Bruce Robert D.,
Versteeg Donald J.
Publication year - 1992
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.5620111014
Subject(s) - statistics , statistical hypothesis testing , statistic , toxicity , fish <actinopterygii> , statistical model , aquatic toxicology , chronic toxicity , toxicology , mathematics , biological system , biology , chemistry , organic chemistry , fishery
Chronic aquatic toxicity test results are commonly analyzed with statistical hypothesis tests to generate summary statistics known as the no‐observed‐effect concentration (NOEC) and first‐observed‐effect concentration (FOEC). These procedures address statistical differences among treatments but suffer several critical limitations. Use of concentration‐response statistics to estimate minimal effect concentrations (i.e., EC values) from quantal and continuous data has advantages over a hypothesis‐testing approach for generating a biologically relevant end point and an estimate of variability from toxicity tests. Estimation of the concentration‐response statistic (EC, effective concentration) for continuous data is not straightforward but is possible with a variety of approaches. A statistical method for estimating EC values described here is based on a nonlinear regression estimation procedure. The usefulness of this method is demonstrated with continuous data from chronic toxicity tests with algae, fish, and invertebrate populations.