Literature DB >> 3303250

Accumulating evidence from independent studies: what we can win and what we can lose.

R J Light.   

Abstract

When asking 'what is known' about a drug or therapy or program at any time, both researchers and practitioners often confront more than a single study. Facing a variety of findings, where conflicts may outweigh agreement, how can a reviewer constructively approach the task? In this discussion, I will outline some questions that can only be answered by examining a group of independent studies. I will also discuss some pitfalls that sometimes swamp the benefits we can gain from synthesis. Most of these pitfalls are avoidable if anticipated early in a review. The benefits of a quantitative review include information about how to match a treatment with the most promising recipients; increasing the statistical power to detect a significant new treatment; telling us when 'contextual effects' are important; helping us to assess the stability and robustness of treatment effectiveness; and informing us when research finds are especially sensitive to investigators' research design. The pitfalls include aggregating data from studies on different populations; aggregating when there is more than one underlying measure of central tendency; and emphasizing an average outcome when partitioning variance gives far more useful information.

Mesh:

Year:  1987        PMID: 3303250     DOI: 10.1002/sim.4780060304

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  Assessment of Publication Bias and Systematic Review Findings in Top-Ranked Otolaryngology Journals.

Authors:  Andrew Ross; Craig Cooper; Harrison Gray; Blake Umberham; Matt Vassar
Journal:  JAMA Otolaryngol Head Neck Surg       Date:  2019-02-01       Impact factor: 6.223

2.  Prevalence of Poor Sleep Quality in Patients With Hypertension in China: A Meta-analysis of Comparative Studies and Epidemiological Surveys.

Authors:  Lin Li; Lu Li; Jing-Xin Chai; Le Xiao; Chee H Ng; Gabor S Ungvari; Yu-Tao Xiang
Journal:  Front Psychiatry       Date:  2020-06-30       Impact factor: 4.157

3.  A re-evaluation of random-effects meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson; David J Spiegelhalter
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2009-01       Impact factor: 2.483

  3 in total

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