Title |
The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study
|
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Published in |
PLOS ONE, October 2011
|
DOI | 10.1371/journal.pone.0025491 |
Pubmed ID | |
Authors |
Kristian Thorlund, Georgina Imberger, Michael Walsh, Rong Chu, Christian Gluud, Jørn Wetterslev, Gordon Guyatt, Philip J. Devereaux, Lehana Thabane |
Abstract |
Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. |
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Geographical breakdown
Country | Count | As % |
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Canada | 1 | 14% |
Unknown | 6 | 86% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 86% |
Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 2% |
Netherlands | 1 | 1% |
France | 1 | 1% |
Peru | 1 | 1% |
Italy | 1 | 1% |
Spain | 1 | 1% |
Denmark | 1 | 1% |
Unknown | 79 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 15 | 17% |
Student > Ph. D. Student | 14 | 16% |
Student > Master | 12 | 14% |
Other | 6 | 7% |
Student > Postgraduate | 6 | 7% |
Other | 18 | 21% |
Unknown | 16 | 18% |
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Agricultural and Biological Sciences | 6 | 7% |
Nursing and Health Professions | 3 | 3% |
Psychology | 3 | 3% |
Mathematics | 3 | 3% |
Other | 10 | 11% |
Unknown | 24 | 28% |