By Tom M. Palmer, Jonathan A. C. Sterne
This assortment presents certain descriptions of either regular and complex meta-analytic tools and their implementation in Stata. Readers will achieve entry to the statistical equipment in the back of the fast raise within the variety of meta-analyses stated within the social technological know-how and scientific literature. The ebook exhibits the best way to behavior and interpret meta-analyses in addition to produce hugely versatile graphical monitors. utilizing meta-regression, it examines purposes for between-study variability in impact estimates. The publication additionally employs complex tools for the meta-analysis of diagnostic try accuracy stories, dose-response meta-analysis, meta-analysis with lacking facts, and multivariate meta-analysis.
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Extra info for Meta-Analysis: An Updated Collection from the Stata Journal
Despite these caveats, this method is better than other, seriously ﬂawed, methods such as testing the signiﬁcance of a treatment eﬀect in each group rather than testing for diﬀerences between the groups. As explained at the start of this section, meta-regression is the best way to examine and test for between-group diﬀerences. 1 User-deﬁned analyses Study weights The wgt(wgtvar ) option allows the studies to be combined by using speciﬁc weights that are deﬁned by the variable wgtvar . The user must ensure that the weights chosen are meaningful.
G. Thompson. 2001. Presenting random eﬀects meta-analyses: where are we going wrong? In 9th International Cochrane Colloquium. Lyon, France. ———. 2004. Controlling the risk of spurious ﬁndings from meta-regression. Statistics in Medicine 23: 1663–1682. Higgins, J. P. , S. G. Thompson, J. J. Deeks, and D. G. Altman. 2003. Measuring inconsistency in meta-analyses. British Medical Journal 327: 557–560. Kirkwood, B. , and J. A. C. Sterne. 2003. Essential Medical Statistics. 2nd ed. Oxford: Blackwell Science.
And J. P. T. Higgins. 2008. Meta-regression in Stata. Stata Journal. Forthcoming. Higgins, J. P. , and S. G. Thompson. 2001. Presenting random eﬀects meta-analyses: where are we going wrong? In 9th International Cochrane Colloquium. Lyon, France. ———. 2004. Controlling the risk of spurious ﬁndings from meta-regression. Statistics in Medicine 23: 1663–1682. Higgins, J. P. , S. G. Thompson, J. J. Deeks, and D. G. Altman. 2003. Measuring inconsistency in meta-analyses. British Medical Journal 327: 557–560.