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NOEC and LOEC (no and lowest observed effect concentrations, respectively) are toxicological concepts derived from analysis of variance (ANOVA), a not very sensitive method that produces ambiguous results and does not provide confidence intervals (CI) of its estimates. For a long time, despite the abundant criticism that such concepts have raised, the field of the ecotoxicology is reticent to abandon them (two possible reasons will be discussed), adducing the difficulty of clear alternatives. However, this work proves that a debugged dose-response (DR) modeling, through explicit algebraic equations, enables two simple options to accurately calculate the CI of substantially lower doses than NOEC. Both ANOVA and DR analyses are affected by the experimental error, response profile, number of observations and experimental design. The study of these effects--analytically complex and experimentally unfeasible--was carried out using systematic simulations with realistic data, including different error levels. Results revealed the weakness of NOEC and LOEC notions, confirmed the feasibility of the proposed alternatives and allowed to discuss the--often violated--conditions that minimize the CI of the parametric estimates from DR assays. In addition, a table was developed providing the experimental design that minimizes the parametric CI for a given set of working conditions. This makes possible to reduce the experimental effort and to avoid the inconclusive results that are frequently obtained from intuitive experimental plans.
Analysis of Variance, No-Observed-Adverse-Effect Level, ANOVA, Models, Statistical, Dose–response models, Dose-Response Relationship, Drug, Confidence intervals, Modeling, Ecotoxicology, NOEC and LOEC, Parametric estimations, Confidence Intervals, Computer Simulation
Analysis of Variance, No-Observed-Adverse-Effect Level, ANOVA, Models, Statistical, Dose–response models, Dose-Response Relationship, Drug, Confidence intervals, Modeling, Ecotoxicology, NOEC and LOEC, Parametric estimations, Confidence Intervals, Computer Simulation
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