A unified Bayesian framework for interval hypothesis testing in clinical trials

arXiv:2402.13890v1 Announce Type: cross
Abstract: The American Statistical Association (ASA) statement on statistical significance and P-values \cite{wasserstein2016asa} cautioned statisticians against making scientific decisions solely on the basis of traditional P-values. The statement delineated key issues with P-values, including a lack of transparency, an inability to quantify evidence in support of the null hypothesis, and an inability to measure the size of an effect or the importance of a result. In this article, we demonstrate that the interval null hypothesis framework …

abstract arxiv association bayesian clinical clinical trials decisions evidence framework hypothesis interval key making significance statistical stat.me stat.ml support testing transparency type values