Tim Morris

Tim Morris is a Director biostatistician in the Statistical Methodology group at Novartis (UK). He works on the development, understanding and evaluation of statistical methods, with the aim of making emerging methods fit-for-use in applications. His interests include estimands, missing data, covariate adjustment in RCTs, and principled sensitivity analyses. Work on these topics led to a general interest in simulation studies. Tim is a core member of EFSPI/PSI Causal Inference special interest group, and a member of the MRC/NIHR Trials Methodology Research Partnership and the Stratos Initiative. He blogs at Statistical Methodology Meanderings.

Title of keynote presentation:

Simulation studies: bringing method to the madness

Abstract:

Simulation studies involve drawing random numbers to understand the properties and behaviour of statistical methods. Statisticians have been using simulation studies since before computers existed (e.g. ‘Student’ in 1908). However, when it comes to simulation studies, we are largely self-taught. It is often hard understand a simulation study, or even its objective. Indeed, the rationale for many simulation studies seems to be ‘that is what other people do’. With the above definition of a simulation study – rather than statistical simulation more generally – we can see a
common structure underlying simulation studies across disparate settings. This talk will sketch the structure before diving into some interesting issues, including choices around data generation, the interplay between mathematical results and simulation studies’ results, searching for truth, the contribution of simulation results to methods’ fitness-for-use, and reporting of complex simulation studies.