Sequential change detection and monitoring of temporal trends in random-effects meta-analysis

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Dogo, Samson Henry, Clark, Allan ORCID: https://orcid.org/0000-0003-2965-8941 and Kulinskaya, Elena (2017) Sequential change detection and monitoring of temporal trends in random-effects meta-analysis. Research Synthesis Methods, 8 (2). 220–235. ISSN 1759-2879

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Abstract

Temporal changes in magnitude of effect sizes reported in many areas of research are a threat to the credibility of the results and conclusions of meta-analysis. Numerous sequential methods for meta-analysis have been proposed to detect changes and monitor trends in effect sizes so that meta-analysis can be updated when necessary and interpreted based on the time it was conducted. The difficulties of sequential meta-analysis under the random-effects model are caused by dependencies in increments introduced by the estimation of the heterogeneity parameter τ2. In this paper we propose the use of a retrospective CUSUM-type test with bootstrap critical values. This method allows retrospective analysis of the past trajectory of cumulative effects in random-effects meta-analysis, and its visualisation on a chart similar to CUSUM chart. Simulation results show that the new method demonstrates good control of Type I error regardless of the number or size of the studies and the amount of heterogeneity. Application of the new method is illustrated on two examples of medical meta-analyses.

Item Type: Article
Additional Information: 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: sequential meta-analysis,cumulative meta-analysis,cusum,bootstrap
Faculty \ School: Faculty of Science > School of Computing Sciences
Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: Pure Connector
Date Deposited: 20 Dec 2016 00:04
Last Modified: 19 Apr 2023 16:31
URI: https://ueaeprints.uea.ac.uk/id/eprint/61777
DOI: 10.1002/jrsm.1222

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