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.
BenjaminiY., and HochbergY.1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B (Methodological)57: 289–300.
2.
BerkeyC. S., HoaglinD. C., MostellerF., and ColditzG. A.1995. A random-effects regression model for meta-analysis. Statistics in Medicine14: 395–411.
3.
Davey SmithG., EggerM., and PhillipsA. N.1997. Meta-analysis: Beyond the grand mean?British Medical Journal315: 1610–1614.
4.
DerSimonianR., and LairdN.1986. Meta-analysis in clinical trials. Controlled Clinical Trials7: 177–188.
5.
DuMouchelW. H., and HarrisJ. E.1983. Bayes methods for combining the results of cancer studies in humans and other species. Journal of the American Statistical Association78: 293–308.
6.
HarrisR. J., BradburnM. J., DeeksJ. J., HarbordR. M., AltmanD. G., and SterneJ. A. C.2008. metan: fixed- and random-effects meta-analysis. Stata Journal8: 3–28.
7.
HarvilleD. A.1977. Maximum likelihood approaches to variance component estimation and to related problems. Journal of the American Statistical Association72: 320–338.
8.
HigginsJ. P. T., and ThompsonS. G.2004. Controlling the risk of spurious findings from meta-regression. Statistics in Medicine23: 1663–1682.
9.
HigginsJ. P. T., ThompsonS. G., DeeksJ. J., and AltmanD. G.2002. Statistical heterogeneity in systematic reviews of clinical trials: A critical appraisal of guidelines and practice. Journal of Health Services Research and Policy7: 51–61.
10.
HigginsJ. P. T., ThompsonS. G., DeeksJ. J., and AltmanD. G.2003. Measuring inconsistency in meta-analyses. British Medical Journal327: 557–560.
11.
HigginsJ. P. T., ThompsonS. G., and SpiegelhalterD. J. Forthcoming. A reevaluation of random-effects meta-analysis. Journal of the Royal Statistics Society, Series A (Statistics in Society).
12.
KnappG., and HartungJ.2003. Improved tests for a random-effects meta-regression with a single covariate. Statistics in Medicine22: 2693–2710.
13.
LawlorD. A., and HopkerS. W.2001. The effectiveness of exercise as an intervention in the management of depression: Systematic review and meta-regression analysis of randomised controlled trials. British Medical Journal322: 763.
14.
LipseyM. W., and WilsonD. B.2001. Practical Meta-Analysis.Thousand Oaks, CA: Sage.
15.
ManlyB. F. J.2006. Randomization, Bootstrap and Monte Carlo Methods in Biology. 3rd ed. Boca Raton, FL: Chapman & Hall/CRC.
16.
MorrisC. N.1983. Parametric empirical Bayes inference: Theory and applications. Journal of the American Statistical Association78: 47–55.
17.
NewsonR., and the ALSPAC Study Team. 2003. Multiple-test procedures and smile plots. Stata Journal3: 109–132.
18.
ShafferJ. P.1995. Multiple hypothesis testing. Annual Review of Psychology46: 561–584.
19.
SharpS.1998. sbe23: Meta-analysis regression. Stata Technical Bulletin42: 16–22. Reprinted in Stata Technical Bulletin Reprints, vol. 7, pp. 148–155. College Station, TX: Stata Press.
20.
SidikK., and JonkmanJ. N.2007. A comparison of heterogeneity variance estimators in combining results of studies. Statistics in Medicine26: 1964–1981.
21.
SterneJ. A. C., and Davey SmithG.2001. Sifting the evidence—what's wrong with significance tests?British Medical Journal322: 226–231.
22.
StoreyJ. D., TaylorJ. E., and SiegmundD.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 (Statistical Methodology)66: 187–205.
23.
SuttonA. J., and HigginsJ. P. T.2008. Recent developments in meta-analysis. Statistics in Medicine27: 625–650.
24.
ThompsonS. G.1993. Controversies in meta-analysis: The case of the trials of serum cholesterol reduction. Statistical Methods in Medical Research2: 173–192.
25.
ThompsonS. G., and HigginsJ. P. T.2002. How should meta-regression analyses be undertaken and interpreted?Statistics in Medicine21: 1559–1573.
26.
ThompsonS. G., and HigginsJ. P. T.2005. Can meta-analysis help target interventions at individuals most likely to benefit?Lancet365: 341–346.
27.
ThompsonS. G., and SharpS. J.1999. Explaining heterogeneity in meta-analysis: A comparison of methods. Statistics in Medicine18: 2693–2708.
28.
WacholderS., ChanockS., Garcia-ClosasM., El ghormliL., and RothmanN.2004. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. JNCI Cancer Spectrum96: 434–442.
29.
WestfallP. H., and YoungS. S.1993. Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment.New York: Wiley.
