Sequential biases in accumulating evidence

Kulinskaya, Elena, Huggins, Richard and Dogo, Samson Henry (2016) Sequential biases in accumulating evidence. Research Synthesis Methods, 7 (3). 294–305. ISSN 1759-2879

[img]
Preview
PDF (Published manuscript) - Published Version
Available under License Creative Commons Attribution.

Download (499kB) | Preview

Abstract

Whilst it is common in clinical trials to use the results of tests at one phase to decide whether to continue to the next phase and to subsequently design the next phase, we show that this can lead to biased results in evidence synthesis. Two new kinds of bias associated with accumulating evidence, termed "sequential decision bias" and "sequential design bias" are identified. Both kinds of bias are the result of making decisions on the usefulness of a new study, or its design, based on the previous studies. Sequential decision bias is determined by the correlation between the value of the current estimated effect and the probability of conducting an additional study. Sequential design bias arises from using the estimated value instead of the clinically relevant value of an effect in sample size calculations. We considered both the fixed effect and the random effects models of meta-analysis, and demonstrated analytically and by simulations that in both settings the problems due to sequential biases are apparent. According to our simulations, the sequential biases increase with increased heterogeneity. Minimisation of sequential biases arises as a new and important research area necessary for successful evidence-based approaches to the development of science.

Item Type: Article
Additional Information: © 2015 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: accumulating evidence,cumulative meta-analysis,sequential meta-analysis,sequential bias
Faculty \ School: Faculty of Science > School of Computing Sciences
Depositing User: Pure Connector
Date Deposited: 22 Jan 2016 11:00
Last Modified: 22 Jul 2020 00:24
URI: https://ueaeprints.uea.ac.uk/id/eprint/56659
DOI: 10.1002/jrsm.1185

Actions (login required)

View Item View Item