Department of Biostatistics Seminar/Workshop Series

Monte Carlo Error Assessment in Statistical Experiments

Elizabeth Koehler, M.S.

Biostatistician II
Department of Biostatistics, Vanderbilt University

Wednesday, April 9, 2008, 1:30-2:30pm, MRBIII Conference Room 1220

Intended Audience: Persons interested in applied statistics, statistical theory, epidemiology, health services research, clinical trials methodology, statistical computing, statistical graphics, R users or potential users

Statistical experiments, more commonly called simulations, are used to study the behavior of statistical methods and measures under controlled conditions. Among several other aims, simulation studies are used to help determine an appropriate sample size, observe the consequences of violating model assumptions, and compare competing methods. Although simulations have become increasingly efficient, they are still based on finite samples and are therefore subject to uncertainty. Reporting either this uncertainty or some justification for the number of replicates, when reporting the results of a simulation study has received little attention. This seminar examines the presence of Monte Carlo error and presents simple, practical methods for estimating Monte Carlo error and the number of replications required to achieve a desired accuracy, which are demonstrated in a short series of simulations.
Topic revision: r2 - 18 Mar 2008, DianeKolb

This site is powered by FoswikiCopyright © 2013-2020 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback