statslausanne

Download

statslausanne@lists.sib.swiss

October 2016

1 participants
2 discussions

two short courses in statistics
by Rousson Valentin 26 Oct '16

26 Oct '16

Dear list members, We shall have two short courses in Statistics involving Stata by Dr. Rose Medeiros on Friday, November 18 on the Biopôle site in Lausanne-North (see the flyer enclosed). First course (10:30-12:00): Analyzing Data with Missing Values in Stata Using Multiple Imputation Second course (14:15-15:45) : Multilevel/Mixes-effects Models in Stata Place : Centre des laboratoires d'Epalinges, chemin des Boveresses 155, 1066 Epalinges Participation is free of charge but registration is mandatory until November 10 via email at formations.sante(a)chuv.ch. Hope to see you there! Patrick and Valentin

1 0

Statistical forum on November 10 at 11:00
by Rousson Valentin 26 Oct '16

26 Oct '16

Dear all, The next seminar in our series of statistics talks for people interested in quantitative methods in biology and medicine will take place on Thursday 10 November 2016 at 11h00, in the Salle Delachaux (Biopôle 2, first floor, Route de la Corniche 10, 1010 Lausanne, M2: Vennes). The speaker will be Dr. Kaspar Rufibach, statistician by Roche, Basel, Switzerland. Title: Bayesian predictive power: update after a blinded interim analysis and choice of prior Abstract: Bayesian predictive power is the expectation of the probability to meet the primary endpoint of a clinical trial, or any statistical test, at the final analysis, where expectation is computed with respect to a prior distribution over the true underlying effect. Bayesian predictive power is thus a way of quantifying the success probability for the trial sponsor while the trial is still running. The existing framework typically assumes that once the trial is not stopped at an interim analysis, Bayesian predictive power is updated with the resulting interim estimate. However, in blinded Phase III trials, typically an independent committee looks at the data and no effect estimate is revealed to the sponsor after passing the interim analysis. Instead, the sponsor only knows that the effect estimate was between predefined futility and efficacy boundaries. In the first part, we show how Bayesian predictive power for a time-to-event endpoint can be updated based on such knowledge only. In the literature it is often suggested to use a Normal prior. In the second part, we show that, unless the prior sample size is large compared to the Phase III trial, using a Normal prior leads to potentially undesired features of Bayesian predictive power that seem to be generally overlooked in applications. This is joint work with Markus Abt, Hans Ulrich Burger, and Paul Jordan (all Roche, Basel). Hope to see you there! Valentin (for the organizers: Jérôme Goudet, Valentin Rousson, Frédéric Schütz) CHUV centre hospitalier universitaire vaudois Valentin ROUSSON - Professeur mathematicien/statisticien Département universitaire de medecine et santé communautaires (DUMSC) Médecine sociale et préventive (IUMSP) Biostatistique et méthodes quantitatives +41 (0)21 314 73 28 TEL Valentin.Rousson(a)chuv.ch<mailto:Valentin.Rousson@chuv.ch> www.chuv.ch<http://www.chuv.ch/>

1 0