In some meta-analyses, we find that small studies have systematically different effects to the large studies. This can have many causes, but one is the possibility of reporting bias - that is, we might be missing small studies with negative effects because they are unpublished or less accessible than larger studies. This slidecast presentation describes how to identify small-study effects and helps you understand reporting biases.
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- Describe how funnel plots can help in identifying small-study effects
- Discuss how sensitivity analysis can highlight the presence of small study effects
- Outline a continuum of dissemination of research results
- Explain how reporting bias can influence the effect estimates in systematic reviews
- Address the problem of reporting bias in systematic reviews
Small study effects and reporting biases - slidecast
Approved by the Cochrane Methods Board on 5 October 2011.
Compiled by Miranda Cumpston, based on materials by Jonathan Sterne, Matthias Egger, Julian Higgins, David Moher, Nancy Santesso, Holger Schünemann, the Cochrane Bias Methods Group, Cochrane Australia, and the Cochrane GRADEing group.