dc.contributor.author Miller, T. dc.contributor.author Hendrie, Delia dc.contributor.author Derzon, J. dc.date.accessioned 2017-01-30T11:30:28Z dc.date.available 2017-01-30T11:30:28Z dc.date.created 2014-10-08T06:00:37Z dc.date.issued 2011 dc.identifier.citation Miller, T. and Hendrie, D. and Derzon, J. 2011. Exact method for computing absolute percent change in a dichotomous outcome from meta-analytic effect size: Improving impact and cost-outcome estimates. Value in Health. 14 (1): pp. 144-151. dc.identifier.uri http://hdl.handle.net/20.500.11937/12391 dc.identifier.doi 10.1016/j.jval.2010.10.013 dc.description.abstract Objectives: Meta-analyses typically compute a treatment effect size (Cohen's d), which is readily converted to another common measure, the binomial effect size display (BESD). BESD is the correlation coefficient and represents a percentage difference in outcome attributable to an intervention. Both d and BESD are in arbitrary units; neither measures the absolute change resulting from intervention. The method used to estimate absolute change from BESD assumes both a 50-50 split of the outcome and a balanced design. Consequently, inaccurate assumptions underpin most meta-analytic estimates of the gain resulting from an intervention (and of its cost effectiveness). This article develops an exact formula without these assumptions. Methods: The formula is developed algebraically from 1) the formula for the correlation coefficient represented as a 2-by-2 contingency table constructed from the relative size of the treatment and control groups and the percentage of people who would have the condition absent intervention, and 2) the BESD correlation coefficient formula showing change in success probability with treatment. Results: Simulation reveals that BESD only approximates the reduction in the outcome an intervention might well achieve when the problem outcome occurs in 35%-65% of cases. For less common outcomes, BESD substantially overestimates the impact of an intervention. Even when BESD accurately estimates the likely percentage change in outcome, it paints a misleading picture of the proportion of cases that will achieve a positive outcome. Conclusion: It is time to retire BESD. Our equations can also guide effect size estimation from difficult articles. dc.publisher Wiley-Blackwell Publishing, Inc. dc.title Exact method for computing absolute percent change in a dichotomous outcome from meta-analytic effect size: Improving impact and cost-outcome estimates dc.type Journal Article dcterms.source.volume 14 dcterms.source.number 1 dcterms.source.startPage 144 dcterms.source.endPage 151 dcterms.source.issn 1098-3015 dcterms.source.title Value in Health curtin.department Centre for Population Health curtin.accessStatus Open access via publisher
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