TY - JOUR

T1 - Expanding the toxicologist's statistical toolbox

T2 - Using effect size estimation and dose-response modelling for holistic assessments instead of generic testing

AU - Kluxen, Felix M.

AU - Jensen, Signe M.

PY - 2021

Y1 - 2021

N2 - It is tempting to base (eco-)toxicological assay evaluation solely on statistical significance tests. The approach is stringent, objective and facilitates binary decisions. However, tests according to null hypothesis statistical testing (NHST) are thought experiments that rely heavily on assumptions. The generic and unreflected application of statistical tests has been called “mindless” by Gigerenzer. While statistical tests have an appropriate application domain, the present work investigates how unreflected testing may affect toxicological assessments. Dunnett multiple-comparison and Williams trend testing and their compatibility intervals are compared with dose-response-modelling in case studies, where data do not follow textbook behavior, nor behave as expected from a toxicological point of view. In such cases, toxicological assessments based only on p-values may be biased and biological evaluations based on plausibility may be prioritized. If confidence in a negative assay outcome cannot be established, further data may be needed for a robust toxicological assessment.

AB - It is tempting to base (eco-)toxicological assay evaluation solely on statistical significance tests. The approach is stringent, objective and facilitates binary decisions. However, tests according to null hypothesis statistical testing (NHST) are thought experiments that rely heavily on assumptions. The generic and unreflected application of statistical tests has been called “mindless” by Gigerenzer. While statistical tests have an appropriate application domain, the present work investigates how unreflected testing may affect toxicological assessments. Dunnett multiple-comparison and Williams trend testing and their compatibility intervals are compared with dose-response-modelling in case studies, where data do not follow textbook behavior, nor behave as expected from a toxicological point of view. In such cases, toxicological assessments based only on p-values may be biased and biological evaluations based on plausibility may be prioritized. If confidence in a negative assay outcome cannot be established, further data may be needed for a robust toxicological assessment.

KW - Benchmark dose

KW - Dose-response modelling

KW - Effect size estimation

KW - Hazard characterization

KW - Hazard identification

KW - Statistical significance

KW - Statistical testing

U2 - 10.1016/j.yrtph.2021.104871

DO - 10.1016/j.yrtph.2021.104871

M3 - Journal article

C2 - 33485925

AN - SCOPUS:85099804752

VL - 121

JO - Regulatory Toxicology and Pharmacology

JF - Regulatory Toxicology and Pharmacology

SN - 0273-2300

M1 - 104871

ER -