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Meta-Analysis: An Updated Collection from the Stata Journal by Tom M. Palmer, Jonathan A. C. Sterne

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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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.

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