Abstract:
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Two frequently asked questions in preclinical translational and discovery research are, Given the data we observed: What is the population effect size? How sure are we about the population effect size? Preclinical animal studies often comprise three independent treatment groups: a control; an inducer which induces a disease condition; and a tool compound which attenuates the induced effect. The Attenuation Ratio Metric, R, quantifies the proportional decrease in population mean response from inducer to inducer + tool compound relative to the window of biological opportunity between population mean responses for the control and the inducer. Specifically, R = (MUinducer+tool - MUinducer) / (MUinducer - MUcontrol). The Bayesian strategy conditions on the observed data and evaluates the strength of observed evidence leveraging posterior probabilities of the Attenuation Ratio. We show that the Bayesian strategy provides a direct, more informative, statistical analysis and decision-making tool than the frequentist sampling-theory-based significance testing procedures currently favored by preclinical scientists. Examples source from MRE back translation studies in mice.
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