The bias to meta-analysis resulting from statistical studies with low statistical power tending to remain unpublished and inaccessible to the analyst.
Publication bias is a bias with regard to what is likely to be published, among what is available to be published. Not all bias is inherently problematic – for instance, a bias against publishing lies is often a desirable bias – but one problematic and much-discussed bias is the tendency of researchers, editors, and pharmaceutical companies to handle the reporting of experimental results that are positive differently from results that are negative or inconclusive, leading to a misleading bias in the overall published literature. This is usually a bias towards reporting significant results, despite the fact that studies with significant results do not appear to be superior to studies with a null result with respect to quality of design. It has been found that statistically significant results are three times more likely to be published than papers affirming a null result. It also has been found that the most common reason for non-publication is an investigator's declining to submit results for publication, a finding that underlines researchers’ role in publication bias phenomena.
U.S. National Library of Medicine
The influence of study results on the chances of publication and the tendency of investigators, reviewers, and editors to submit or accept manuscripts for publication based on the direction or strength of the study findings. Publication bias has an impact on the interpretation of clinical trials and meta-analyses. Bias can be minimized by insistence by editors on high-quality research, thorough literature reviews, acknowledgement of conflicts of interest, modification of peer review practices, etc.
The numerical value of publication bias in Chaldean Numerology is: 3
The numerical value of publication bias in Pythagorean Numerology is: 9
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"publication bias." Definitions.net. STANDS4 LLC, 2017. Web. 26 Jun 2017. <http://www.definitions.net/definition/publication bias>.