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      An Approach for Addressing the Multiple Testing Problem in Social Policy Impact Evaluations

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      Evaluation Review
      SAGE Publications

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          Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation.

          Large pragmatic trials provide the most reliable data about the effects of treatments, but should be designed, analysed, and reported to enable the most effective use of treatments in routine practice. Subgroup analyses are important if there are potentially large differences between groups in the risk of a poor outcome with or without treatment, if there is potential heterogeneity of treatment effect in relation to pathophysiology, if there are practical questions about when to treat, or if there are doubts about benefit in specific groups, such as elderly people, which are leading to potentially inappropriate undertreatment. Analyses must be predefined, carefully justified, and limited to a few clinically important questions, and post-hoc observations should be treated with scepticism irrespective of their statistical significance. If important subgroup effects are anticipated, trials should either be powered to detect them reliably or pooled analyses of several trials should be undertaken. Formal rules for the planning, analysis, and reporting of subgroup analyses are proposed.
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            A sequentially rejective test procedure based on a modified Bonferroni inequality

            DROR ROM (1990)
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              Weighting systems for linear functions of correlated variables when there is no dependent variable

              S. Wilks (1938)
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                Author and article information

                Journal
                Evaluation Review
                Eval Rev
                SAGE Publications
                0193-841X
                1552-3926
                October 19 2009
                December 2009
                November 10 2009
                December 2009
                : 33
                : 6
                : 539-567
                Affiliations
                [1 ]Mathematica Policy Research, Inc., Princeton, New Jersey,
                Article
                10.1177/0193841X09350590
                b87fee02-e049-4925-85c3-490b62034063
                © 2009

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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