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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.
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