Search Results - "Research synthesis methods"

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  1. 1

    Risk‐of‐bias VISualization (robvis): An R package and Shiny web app for visualizing risk‐of‐bias assessments by McGuinness, Luke A., Higgins, Julian P. T.

    Published in Research synthesis methods (01-01-2021)
    “…Despite a major increase in the range and number of software offerings now available to help researchers produce evidence syntheses, there is currently no…”
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    Journal Article
  2. 2

    Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources by Gusenbauer, Michael, Haddaway, Neal R.

    Published in Research synthesis methods (01-03-2020)
    “…Rigorous evidence identification is essential for systematic reviews and meta‐analyses (evidence syntheses) because the sample selection of relevant studies…”
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  3. 3

    Meta‐analysis and Mendelian randomization: A review by Bowden, Jack, Holmes, Michael V.

    Published in Research synthesis methods (01-12-2019)
    “…Mendelian randomization (MR) uses genetic variants as instrumental variables to infer whether a risk factor causally affects a health outcome. Meta‐analysis…”
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  4. 4

    A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analyses by Langan, Dean, Higgins, Julian P.T., Jackson, Dan, Bowden, Jack, Veroniki, Areti Angeliki, Kontopantelis, Evangelos, Viechtbauer, Wolfgang, Simmonds, Mark

    Published in Research synthesis methods (01-03-2019)
    “…Studies combined in a meta‐analysis often have differences in their design and conduct that can lead to heterogeneous results. A random‐effects model accounts…”
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  5. 5

    Basics of Meta-Analysis: "I"[superscript 2] Is Not an Absolute Measure of Heterogeneity by Borenstein, Michael, Higgins, Julian P. T, Hedges, Larry V, Rothstein, Hannah R

    Published in Research synthesis methods (01-03-2017)
    “…When we speak about heterogeneity in a meta-analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention…”
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  6. 6

    Optimally estimating the sample standard deviation from the five‐number summary by Shi, Jiandong, Luo, Dehui, Weng, Hong, Zeng, Xian‐Tao, Lin, Lu, Chu, Haitao, Tong, Tiejun

    Published in Research synthesis methods (01-09-2020)
    “…When reporting the results of clinical studies, some researchers may choose the five‐number summary (including the sample median, the first and third…”
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  7. 7

    Seriously misleading results using inverse of Freeman‐Tukey double arcsine transformation in meta‐analysis of single proportions by Schwarzer, Guido, Chemaitelly, Hiam, Abu‐Raddad, Laith J., Rücker, Gerta

    Published in Research synthesis methods (01-09-2019)
    “…Standard generic inverse variance methods for the combination of single proportions are based on transformed proportions using the logit, arcsine, and…”
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  8. 8

    Introduction, comparison, and validation of Meta‐Essentials: A free and simple tool for meta‐analysis by Suurmond, Robert, Rhee, Henk, Hak, Tony

    Published in Research synthesis methods (01-12-2017)
    “…We present a new tool for meta‐analysis, Meta‐Essentials, which is free of charge and easy to use. In this paper, we introduce the tool and compare its…”
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  9. 9

    Basics of meta‐analysis: I2 is not an absolute measure of heterogeneity by Borenstein, Michael, Higgins, Julian P. T., Hedges, Larry V., Rothstein, Hannah R.

    Published in Research synthesis methods (01-03-2017)
    “…When we speak about heterogeneity in a meta‐analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention…”
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    Journal Article
  10. 10

    Methods to estimate the between-study variance and its uncertainty in meta-analysis by Veroniki, Areti Angeliki, Jackson, Dan, Viechtbauer, Wolfgang, Bender, Ralf, Bowden, Jack, Knapp, Guido, Kuss, Oliver, Higgins, Julian PT, Langan, Dean, Salanti, Georgia

    Published in Research synthesis methods (01-03-2016)
    “…Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically…”
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  11. 11

    Meta‐analysis of prevalence: I2 statistic and how to deal with heterogeneity by Migliavaca, Celina Borges, Stein, Cinara, Colpani, Verônica, Barker, Timothy Hugh, Ziegelmann, Patricia Klarmann, Munn, Zachary, Falavigna, Maicon

    Published in Research synthesis methods (01-05-2022)
    “…Over the last decade, there has been a 10‐fold increase in the number of published systematic reviews of prevalence. In meta‐analyses of prevalence, the…”
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  12. 12

    Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide by Marshall, Iain J., Noel‐Storr, Anna, Kuiper, Joël, Thomas, James, Wallace, Byron C.

    Published in Research synthesis methods (01-12-2018)
    “…Machine learning (ML) algorithms have proven highly accurate for identifying Randomized Controlled Trials (RCTs) but are not used much in practice, in part…”
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  13. 13

    Power analysis for random‐effects meta‐analysis by Jackson, Dan, Turner, Rebecca

    Published in Research synthesis methods (01-09-2017)
    “…One of the reasons for the popularity of meta‐analysis is the notion that these analyses will possess more power to detect effects than individual studies…”
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  14. 14

    A scoping review of scoping reviews: advancing the approach and enhancing the consistency by Pham, Mai T., Rajić, Andrijana, Greig, Judy D., Sargeant, Jan M., Papadopoulos, Andrew, McEwen, Scott A.

    Published in Research synthesis methods (01-12-2014)
    “…Background The scoping review has become an increasingly popular approach for synthesizing research evidence. It is a relatively new approach for which a…”
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  15. 15

    Citationchaser: A tool for transparent and efficient forward and backward citation chasing in systematic searching by Haddaway, Neal R., Grainger, Matthew J., Gray, Charles T.

    Published in Research synthesis methods (01-07-2022)
    “…Systematic searching aims to find all possibly relevant research from multiple sources, the basis for an unbiased and comprehensive evidence base. Along with…”
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  16. 16

    MetaInsight: An interactive web‐based tool for analyzing, interrogating, and visualizing network meta‐analyses using R‐shiny and netmeta by Owen, Rhiannon K., Bradbury, Naomi, Xin, Yiqiao, Cooper, Nicola, Sutton, Alex

    Published in Research synthesis methods (01-12-2019)
    “…Background Network meta‐analysis (NMA) is a powerful analysis method used to identify the best treatments for a condition and is used extensively by health…”
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  17. 17

    Investigating and dealing with publication bias and other reporting biases in meta‐analyses of health research: A review by Page, Matthew J., Sterne, Jonathan A. C., Higgins, Julian P. T., Egger, Matthias

    Published in Research synthesis methods (01-03-2021)
    “…A P value, or the magnitude or direction of results can influence decisions about whether, when, and how research findings are disseminated. Regardless of…”
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  18. 18

    Testing for funnel plot asymmetry of standardized mean differences by Pustejovsky, James E., Rodgers, Melissa A.

    Published in Research synthesis methods (01-03-2019)
    “…Publication bias and other forms of outcome reporting bias are critical threats to the validity of findings from research syntheses. A variety of methods have…”
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  19. 19

    Introduction to PRISMA 2020 and implications for research synthesis methodologists by Page, Matthew J., Moher, David, McKenzie, Joanne E.

    Published in Research synthesis methods (01-03-2022)
    “…Systematic reviews should be reported completely and accurately so that users can interpret and appraise the review findings appropriately. In this commentary,…”
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  20. 20

    The orchard plot: Cultivating a forest plot for use in ecology, evolution, and beyond by Nakagawa, Shinichi, Lagisz, Malgorzata, O'Dea, Rose E., Rutkowska, Joanna, Yang, Yefeng, Noble, Daniel W. A., Senior, Alistair M.

    Published in Research synthesis methods (01-01-2021)
    “…“Classic” forest plots show the effect sizes from individual studies and the aggregate effect from a meta‐analysis. However, in ecology and evolution,…”
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