Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 1: Results from simulations with constant sample sizes
Methodology
2020-07-06 v2
Abstract
Contemporary statistical publications rely on simulation to evaluate performance of new methods and compare them with established methods. In the context of meta-analysis of log-odds-ratios, we investigate how the ways in which simulations are implemented affect such conclusions. Choices of distributions for sample sizes and/or control probabilities considerably affect conclusions about statistical methods. Here we report on the results for constant sample sizes. Our two subsequent publications will cover normally and uniformly distributed sample sizes.
Keywords
Cite
@article{arxiv.2006.16638,
title = {Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 1: Results from simulations with constant sample sizes},
author = {Elena Kulinskaya and David C. Hoaglin and Ilyas Bakbergenuly},
journal= {arXiv preprint arXiv:2006.16638},
year = {2020}
}
Comments
8 pages and full simulation results, comprising 400 figures, each presenting 12 combinations of sample sizes and numbers of studies