title: Sequential methods for random-effects meta-analysis.
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.
authors.affiliation: MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, U.K. julian.higgins@mrc-bsu.cam.ac.uk
authors.forename: Julian P T
authors.initials: JP
authors.lastname: Higgins
authors.forename: Anne
authors.initials: A
authors.lastname: Whitehead
authors.forename: Mark
authors.initials: M
authors.lastname: Simmonds
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016558:Hemostasis, Endoscopic; D006801:Humans; D015201:Meta-Analysis as Topic; D010438:Peptic Ulcer Hemorrhage / Q000628:therapy; D011446:Prospective Studies