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      The effect direction plot revisited: Application of the 2019 Cochrane Handbook guidance on alternative synthesis methods

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          Abstract

          Effect direction (evidence to indicate improvement, deterioration, or no change in an outcome) can be used as a standardized metric which enables the synthesis of diverse effect measures in systematic reviews. The effect direction (ED) plot was developed to support the synthesis and visualization of effect direction data. Methods for the ED plot require updating in light of new Cochrane guidance on alternative synthesis methods. To update the ED plot, statistical significance was removed from the algorithm for within‐study synthesis and use of a sign test was considered to examine whether patterns of ED across studies could be due to chance alone. The revised methods were applied to an existing Cochrane review of the health impacts of housing improvements. The revised ED plot provides a method of data visualization in synthesis without meta‐analysis that incorporates information about study characteristics and study quality, using ED as a common metric, without relying on statistical significance to combine outcomes of single studies. The results of sign tests, when appropriate, suggest caution in over‐interpreting apparent patterns in effect direction, especially when the number of included studies is small. The revised ED plot meets the need for alternative methods of synthesis and data visualization when meta‐analysis is not possible, enabling a transparent link between the data and conclusions of a systematic review. ED plots may be particularly useful in reviews that incorporate nonrandomized studies, complex systems approaches, and diverse sources of evidence, due to the variety of study designs and outcomes in such reviews.

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          Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline

          In systematic reviews that lack data amenable to meta-analysis, alternative synthesis methods are commonly used, but these methods are rarely reported. This lack of transparency in the methods can cast doubt on the validity of the review findings. The Synthesis Without Meta-analysis (SWiM) guideline has been developed to guide clear reporting in reviews of interventions in which alternative synthesis methods to meta-analysis of effect estimates are used. This article describes the development of the SWiM guideline for the synthesis of quantitative data of intervention effects and presents the nine SWiM reporting items with accompanying explanations and examples.
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            Sifting the evidence-what's wrong with significance tests?

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              Rating the certainty in evidence in the absence of a single estimate of effect

              When studies measure or report outcomes differently, it may not be feasible to pool data across studies to generate a single effect estimate (ie, perform meta-analysis). Instead, only a narrative summary of the effect across different studies might be available. Regardless of whether a single pooled effect estimate is generated or whether data are summarised narratively, decision makers need to know the certainty in the evidence in order to make informed decisions. In this guide, we illustrate how to apply the constructs of the GRADE (Grading of Recommendation, Assessment, Development and Evaluation) approach to assess the certainty in evidence when a meta-analysis has not been performed and data were summarised narratively.
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                Author and article information

                Contributors
                michele.hiltonboon@glasgow.ac.uk
                Journal
                Res Synth Methods
                Res Synth Methods
                10.1002/(ISSN)1759-2887
                JRSM
                Research Synthesis Methods
                John Wiley and Sons Inc. (Hoboken )
                1759-2879
                1759-2887
                05 October 2020
                January 2021
                : 12
                : 1 , Data Visualization for Evidence Synthesis ( doiID: 10.1002/jrsm.v12.1 )
                : 29-33
                Affiliations
                [ 1 ] MRC/CSO Social and Public Health Sciences Unit University of Glasgow Glasgow UK
                Author notes
                [*] [* ] Correspondence

                Michele Hilton Boon, MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 200 Renfield Street, Glasgow G2 3AX, UK.

                Email: michele.hiltonboon@ 123456glasgow.ac.uk

                Author information
                https://orcid.org/0000-0002-2240-7923
                Article
                JRSM1458
                10.1002/jrsm.1458
                7821279
                32979023
                50a95f5e-dc0d-4fe4-a6ae-31ff5f61bf90
                © 2020 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 February 2020
                : 01 August 2020
                : 23 September 2020
                Page count
                Figures: 1, Tables: 0, Pages: 5, Words: 2757
                Funding
                Funded by: Medical Research Council , open-funder-registry 10.13039/501100007155;
                Award ID: MC_UU_12017/15
                Funded by: Scottish Government Chief Scientist Office
                Award ID: SPHSU15
                Categories
                Special Issue Paper
                Special Issue Papers
                Custom metadata
                2.0
                January 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.6 mode:remove_FC converted:22.01.2021

                data visualization,effect direction,standardized metric,synthesis,vote counting

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