IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v8y2008i4p493-519.html
   My bibliography  Save this article

Meta-regression in Stata

Author

Listed:
  • Roger M. Harbord

    (University of Bristol)

  • Julian P.T. Higgins

    (MRC Biostatistics Unit, Cambridge, UK)

Abstract

We present a revised version of the metareg command, which performs meta-analysis regression (meta-regression) on study-level summary data. The major revisions involve improvements to the estimation methods and the addition of an option to use a permutation test to estimate p-values, including an adjustment for multiple testing. We have also made additions to the output, added an option to produce a graph, and included support for the predict command. Stata 8.0 or above is required. Copyright 2008 by StataCorp LP.

Suggested Citation

  • Roger M. Harbord & Julian P.T. Higgins, 2008. "Meta-regression in Stata," Stata Journal, StataCorp LP, vol. 8(4), pages 493-519, December.
  • Handle: RePEc:tsj:stataj:v:8:y:2008:i:4:p:493-519
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=sbe23_1
    Download Restriction: no

    File URL: http://www.stata-journal.com/software/sj8-4/sbe23_1
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ross J. Harris & Michael J. Bradburn & Jonathan J. Deeks & Roger M. Harbord & Douglas G. Altman & Jonathan A. C. Sterne, 2008. "metan: fixed- and random-effects meta-analysis," Stata Journal, StataCorp LP, vol. 8(1), pages 3-28, February.
    2. Roger Newson & The ALSPAC Study Team, 2003. "Multiple-test procedures and smile plots," Stata Journal, StataCorp LP, vol. 3(2), pages 109-132, June.
    3. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zabaloy, Maria Florencia & Viego, Valentina, 2022. "Household electricity demand in Latin America and the Caribbean: A meta-analysis of price elasticity," Utilities Policy, Elsevier, vol. 75(C).
    2. Jianqing Fan & Xu Han, 2017. "Estimation of the false discovery proportion with unknown dependence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1143-1164, September.
    3. Shigeyuki Matsui & Hisashi Noma, 2011. "Estimating Effect Sizes of Differentially Expressed Genes for Power and Sample-Size Assessments in Microarray Experiments," Biometrics, The International Biometric Society, vol. 67(4), pages 1225-1235, December.
    4. Lianming Wang & David B. Dunson, 2010. "Semiparametric Bayes Multiple Testing: Applications to Tumor Data," Biometrics, The International Biometric Society, vol. 66(2), pages 493-501, June.
    5. Hanck, Christoph, 2011. "Now, whose schools are really better (or weaker) than Germany's? A multiple testing approach," Economic Modelling, Elsevier, vol. 28(4), pages 1739-1746, July.
    6. Ghosh Debashis, 2012. "Incorporating the Empirical Null Hypothesis into the Benjamini-Hochberg Procedure," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-21, July.
    7. Dean Palejev & Mladen Savov, 2021. "On the Convergence of the Benjamini–Hochberg Procedure," Mathematics, MDPI, vol. 9(17), pages 1-19, September.
    8. Moon, H.R. & Perron, B., 2012. "Beyond panel unit root tests: Using multiple testing to determine the nonstationarity properties of individual series in a panel," Journal of Econometrics, Elsevier, vol. 169(1), pages 29-33.
    9. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    10. Colin Sumpter & Belen Torondel, 2013. "A Systematic Review of the Health and Social Effects of Menstrual Hygiene Management," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    11. G�nther Fink & Margaret McConnell & Sebastian Vollmer, 2014. "Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(1), pages 44-57, January.
    12. Thorsten Dickhaus & Jakob Gierl, 2012. "Simultaneous test procedures in terms of p-value copulae," SFB 649 Discussion Papers SFB649DP2012-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Dette, Holger & Hoderlein, Stefan & Neumeyer, Natalie, 2016. "Testing multivariate economic restrictions using quantiles: The example of Slutsky negative semidefiniteness," Journal of Econometrics, Elsevier, vol. 191(1), pages 129-144.
    14. Gharad Bryan & James J Choi & Dean Karlan, 2021. "Randomizing Religion: the Impact of Protestant Evangelism on Economic Outcomes," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(1), pages 293-380.
    15. Dennis Guignet & Matthew T. Heberling & Michael Papenfus & Olivia Griot, 2022. "Property Values, Water Quality, and Benefit Transfer: A Nationwide Meta-analysis," Land Economics, University of Wisconsin Press, vol. 98(2), pages 191-218.
    16. Wang Chamont & Gevertz Jana L., 2016. "Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(4), pages 321-347, August.
    17. de Uña-Alvarez Jacobo, 2011. "On the Statistical Properties of SGoF Multitesting Method," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-30, April.
    18. Ferreira José A. & Berkhof Johannes & Souverein Olga & Zwinderman Koos, 2009. "A Multiple Testing Approach to High-Dimensional Association Studies with an Application to the Detection of Associations between Risk Factors of Heart Disease and Genetic Polymorphisms," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-56, January.
    19. Huang, Rong & Pilbeam, Keith & Pouliot, William, 2021. "Do actively managed US mutual funds produce positive alpha?," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 472-492.
    20. Baolin Wu & Zhong Guan & Hongyu Zhao, 2006. "Parametric and Nonparametric FDR Estimation Revisited," Biometrics, The International Biometric Society, vol. 62(3), pages 735-744, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:8:y:2008:i:4:p:493-519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.