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Comparative Study
. 2011 Apr 30;30(9):903-21.
doi: 10.1002/sim.4088. Epub 2010 Dec 28.

Sequential methods for random-effects meta-analysis

Julian P T Higgins  1 , Anne Whitehead, Mark Simmonds
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Free PMC article
Comparative Study

Sequential methods for random-effects meta-analysis

Julian P T Higgins et al. Stat Med. .
Free PMC article

Abstract

Although meta-analyses are typically viewed as retrospective activities, they are increasingly being applied prospectively to provide up-to-date evidence on specific research questions. When meta-analyses are updated account should be taken of the possibility of false-positive findings due to repeated significance tests. We discuss the use of sequential methods for meta-analyses that incorporate random effects to allow for heterogeneity across studies. We propose a method that uses an approximate semi-Bayes procedure to update evidence on the among-study variance, starting with an informative prior distribution that might be based on findings from previous meta-analyses. We compare our methods with other approaches, including the traditional method of cumulative meta-analysis, in a simulation study and observe that it has Type I and Type II error rates close to the nominal level. We illustrate the method using an example in the treatment of bleeding peptic ulcers.

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Figures

Figure 1
Figure 1
Sequential fixed-effect meta-analysis of peptic ulcers data.
Figure 2
Figure 2
Random-effects meta-analysis and naïve random-effects cumulative meta-analysis of peptic ulcers data.
Figure 3
Figure 3
Sequential meta-analysis of peptic ulcers data.
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