Dear all, Another seminar in our series of statistics talks for people interested in quantitative methods in biology and medicine will take place on Thursday 18 October 2018 at 11:00, in the Salle Delachaux (Biopôle 2, first floor, Route de la Corniche 10, 1010 Lausanne, M2: Vennes), which I will present. Title: A five-decision testing procedure to infer the value of a unidimensional parameter Abstract: A statistical test can be seen as a procedure to produce a decision based on observed data, where some decisions consist of rejecting a hypothesis (yielding a significant result) and some do not, and where one controls the probability to make a wrong rejection at some pre-specified significance level. Whereas traditional hypothesis testing involves only two possible decisions (to reject or not a null hypothesis), Kaiser's directional two-sided test as well as the more recently introduced testing procedure of Jones and Tukey, each equivalent to running two one-sided tests, involve three possible decisions to infer the value of a unidimensional parameter. The latter procedure assumes that a point null hypothesis is impossible (e.g., that two treatments cannot have exactly the same effect), allowing a gain of statistical power. There are, however, situations where a point hypothesis is indeed plausible, for example, when considering hypotheses derived from Einstein's theories. In this article, we introduce a five-decision rule testing procedure, which combines the advantages of the testing procedures of Kaiser (no assumption on a point hypothesis being impossible) and Jones and Tukey (higher power), allowing for a non-negligible (typically 20%) reduction of the sample size needed to reach a given statistical power to get a significant result, compared to the traditional approach, while achieving "the abolition one and for all of the controversy over whether a one-sided or a two-sided test is appropriate", as L. Freedman once said. This is a joint work with Aaron McDaid and Zoltan Kutalik (IUMSP) (see the enclosed publication) Hope to see you there! Valentin (for the organizers: Zoltán Kutalik, Valentin Rousson, Frédéric Schütz) CHUV centre hospitalier universitaire vaudois Valentin ROUSSON - Professeur associé, mathematicien/statisticien Département universitaire de medecine et santé communautaires (DUMSC) Médecine sociale et préventive (IUMSP) Biostatistique et méthodes quantitatives BIO 2/2ème/103 Rte de la Corniche 10, CH - 1010 Lausanne +41 (0)21 314 73 28 TEL Valentin.Rousson@chuv.chmailto:Valentin.Rousson@chuv.ch www.chuv.chhttp://www.chuv.ch/