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METAN: Stata module for fixed and random effects meta-analysis

Author

Listed:
  • David Fisher

    (MRC Clinical Trials Unit at UCL)

  • Ross Harris

    (Department of Social Medicine, University of Bristol)

  • Mike Bradburn

    (Centre for Statistics in Medicine, University of Oxford)

  • Jon Deeks

    (Centre for Statistics in Medicine, University of Oxford)

  • Roger Harbord

    (Department of Social Medicine, University of Bristol)

  • Doug Altman

    (Centre for Statistics in Medicine, University of Oxford)

  • Thomas Steichen

    (Department of Social Medicine, University of Bristol)

  • Jonathan Sterne

    (Department of Social Medicine, University of Bristol)

  • Julian Higgins

    (Department of Social Medicine, University of Bristol)

Programming Language

Stata

Abstract

Meta-analysis is a statistical technique for combining results from multiple independent studies, with the aim of estimating a single overall effect. The routines in this package provide facilities to conduct meta-analyses of binary (event) or continuous data from two groups, or intervention effect estimates with corresponding standard errors or confidence intervals. This is an updated version of metan as published in Stata Journal Issue 8, and prior to that in STB-44, authored by Michael J Bradburn, Jonathan J Deeks and Douglas G Altman. Updates include a wide range of random-effects models; cumulative and influence analysis; meta-analysis of proportions; and better handling of heterogeneity, continuity correction and returned values. The routine for constructing forest plots has been separated off (‘forestplot’ command) and hugely extended; extremely flexible and generalised forest plots may now be produced. Also included is an “immediate” command ‘metani’, which accepts numlists or matrices as input rather than variables in memory; the ‘metannt’ program for binary data, which displays estimated intervention effects in terms of the absolute reduction in risk and number needed to treat; and the ‘labbe’ program which produces L'Abbe plots to examine whether the assumption of a common odds ratio, risk ratio or risk difference is reasonable. Further information on this package, including validation scripts, may be found at https://github.com/UCL/metan; and a description of available Stata meta-analysis commands may be found at http://www.stata.com/support/faqs/stat/meta.html.

Suggested Citation

  • David Fisher & Ross Harris & Mike Bradburn & Jon Deeks & Roger Harbord & Doug Altman & Thomas Steichen & Jonathan Sterne & Julian Higgins, 2006. "METAN: Stata module for fixed and random effects meta-analysis," Statistical Software Components S456798, Boston College Department of Economics, revised 19 Sep 2023.
    • Handle: RePEc:boc:bocode:s456798
    Note: This module should be installed from within Stata by typing "ssc install metan". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

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