It's time! Ten reasons to start replicating simulation studies

Frontiers in Epidemiology, vol. 2, pp. 973470

Abstract

The quantitative analysis of research data is a core element of empirical research. The performance of statistical methods that are used for analyzing empirical data can be evaluated and compared using computer simulations. A single simulation study can influence the analyses of thousands of empirical studies to follow. With great power comes great responsibility. Here, we argue that this responsibility includes replication of simulation studies to ensure a sound foundation for data analytical decisions. Furthermore, being designed, run, and reported by humans, simulation studies face challenges similar to other experimental empirical research and hence should not be exempt from replication attempts. We highlight that the potential replicability of simulation studies is an opportunity quantitative methodology as a field should pay more attention to.

Authors 3

1. Oscar Lorenzo Olvera Astivia

   University of Washington

   Affiliation as printed

   College of Education, University of Washington, Seattle, WA, United States

2. Tim Peter Morris

   University College London · MRC Clinical Trials Unit at UCL

   Affiliation as printed

   MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom

3. Rolf H. H. Groenwold corresponding Aachen Department of Biomedical Data Sciences Department of Clinical Epidemiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands

   Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands