Speaker
Description
In toxicology, concentration-response experiments are conducted to investigate the toxic behaviour of a given substance. Typically, a parametric model is fitted and effective concentrations to a viability level p (EC_p) are estimated which are used e.g. in further experiments. However, in previous research, it was observed that the estimated EC_p of the same experiment conducted in the same manner on different days differ substantially. The question arises whether regular variability within the experimental day can explain these differences, or whether there are structural changes, so called day-to-day effects, between the different days.
To detect potential day-to-day effects, we evaluate the EC_p of one day and the corresponding viability of another day at this concentration as a nested function and derive the asymptotic distribution. We use this result to construct appropriate confidence intervals (CIs) and hypotheses tests. Starting with the situation, in which two different experimental days are considered, we generalize the results to the situation of several experimental days using the Dunnet-procedure. An extensive simulation study evaluates the developed methods. Moreover, we apply the testing procedure to a real cytotoxicity dataset to detect potential day-to-day effects.
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