Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 1: Results from simulations with constant sample sizes

2020/06/30 by Elena Kulinskaya, Kulinskaya, Elena, David C. Hoaglin +3
Decision Sciences · Mathematics · #FOS: Computer and information sciences #Meta-analysis and systematic reviews #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials

paper · pdf · doi:10.48550/arxiv.2006.16638

openalex publication_date 2020/06/30 · openalex created_date 2020/07/10 · openalex updated_date 2026/07/28

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.

Citations

• Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data

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