"The central problem in management and leadership is failure to understand the information in variation." Lloyd S Nelson as quoted by WE Deming

The pharmaceutical industry has both made a success and a failure of dealing with variation. It has become adept at designing trials that can deliver good signals against a background of variation. However, too often it has accepted measurement approaches that increase the variation and has done much less well in understanding that variation. Amongst the side-effects, has been an overestimate of the scope for personalising medicine. In this lecture Senn will claim that one of the lost opportunities of studying the effects of treatment has been using intelligent statistical approaches to decomposing variance and, in order to do better, that we should pay close attention to what others have been doing to try and tame variation in health care delivery.

The content of the lecture will be appeal to both a scientific & clinical research audience as well as to a statistical audience. Places are limited, so please sign up early to ensure your place. You will receive a reminder of the date, time & location nearer the date.

Hosted by Statsols, this complimentary lecture will take place at Hayfield Manor Hotel Cork, Ireland on Wednesday February 22nd 2017 at 10:00am.

About Professor Stephen Senn

Stephen Senn.jpgCurrently Head of Competence Centre for Methodology and Statistics with the Luxembourg Institute of Health, Stephen Senn was previously Professor of Statistics at a number of UK universities as well as holding senior statistical roles in the Swiss pharmaceutical industry.

He has written numerous papers in the area of healthcare statistics, and three books; Statistical Issues in Drug Development (Wiley: 1997,2007), Dicing with Death (Cambridge: 2003) and Crossover Trials in Clinical Research (Wiley: 1993,2002).

He is recognised as a leading global authority on clinical biostatistics. Stephen Senn is a former member of the Statsols statistical advisory board and he currently serves as a consultant to our statistical development team.