This paper investigates the results of simulations from which clustered binary dose-response data are generated. This data mimics the type of discrete data collected from experiments conducted in developmental toxicity studies on animals. In particular one assumption used in the design of these simulations is that hormesis exists, as evidenced by the dose-response pattern of the generated data. This implies the existence of a threshold level, as hormesis, if it exists, would exist below this level. Below the threshold level, no adverse effects above the response at the control dose level should exist. While hormesis implies several dose-response patterns below threshold, in this paper, the hormetic pattern is assumed to be U-shaped. Improving upon the design of current and past developmental studies, these simulations also include designs in which dose levels and litters (clusters of animals) are allocated in a way that increases the power for detecting hormesis, assuming it exists. The beta-binomial distribution is used to model the clustered binary data that results from responses of animals in the same litter. The results of these simulations will indicate that by altering current designs of developmental studies, this improves the ability to detect hormesis.
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Daniel Hunt (2002) studied this question.
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