Publication bias arises from the tendency for researchers and editors to handle experimental results that are positive (they found something) differently from results that are negative (found that something did not happen) or inconclusive.
Publication bias has been documented to occur in studies of medical interventions. Publication bias, or the related outcome reporting bias (see below), may occur in 25% to 60% of some types of articles.
Publication bias may also occur in studies of diagnostic tests. Publication bias may be more of a problem in diagnostic test research than in randomized controlled trials because studies of diagnostic tests can be secondary analyses of databases and do not have to be registered prior to publication.
- "Publication bias occurs when the publication of research results depends on their nature and direction."
Positive results bias, a type of publication bias, occurs when authors are more likely to submit, or editors accept, positive than null (negative or inconclusive) results. A related term, "the file drawer problem", refers to the tendency for those negative or inconclusive results to remain hidden and unpublished. Even a small number of studies lost in the file drawer can result in a significant bias..
Selective reporting bias, or outcome reporting bias, occurs when several outcomes within a trial are measured but these are reported selectively depending on the strength and direction of those results. Related terms that have been coined are p-hacking and HARKing (Hypothesizing After the Results are Known).
Omitted-variable bias occurs when an "adjusting variable has an own effect on the dependent variable and is correlated with the variable of interest, excluding this adjusting variable from the regression induces omitted-variable bias".
Small study effect
The small study effect is closely related. The small study effect is the observation that small studies tend to report more positive results. This is especially a threat when the original studies in a meta-analysis are less than 50 patients in size.
Suppose that several studies about the influence of power lines on cancer are performed. They are admitted for publication only if they show a correlation with a 95% confidence level. If only the positive results make it to publication, because negative results are just shelved, we do not know how many studies were performed, so it is possible that all the published results are type I errors.
The caliper test may be able to detect publication biases
Effect on meta-analysis
The effect of this is that published studies may not be truly representative of all valid studies undertaken, and this bias may distort meta-analyses and systematic reviews of large numbers of studies - on which evidence-based medicine, for example, increasingly relies. The problem may be particularly significant when the research is sponsored by entities that may have a financial interest in achieving favourable results.
Those undertaking meta-analyses and systematic reviews need to take account of publication bias in the methods they use for identifying the studies to include in the review. Among other techniques to minimise the effects of publication bias, they may need to perform a thorough search for unpublished studies, and to use such analytical tools as a funnel plot to quantify the effects of bias.
An example of probable publication bias is in the studies of glucosamine and chondroitin for treatment of osteoarthritis. In an initial meta-analysis, the authors noted evidence of publication bias during examination of the results. A subsequent large randomized controlled trial and meta-analyses including the large trial were negative.
One study compared Chinese and non-Chinese studies of gene-disease associations and found that "Chinese studies in general reported a stronger gene-disease association and more frequently a statistically significant result". One possible interpretation of this result is selective publication (publication bias).
Ioannidis has inventoried factors that should alert readers to risks of publication bias .
In September 2004, editors of several prominent medical journals (including the New England Journal of Medicine, The Lancet, Annals of Internal Medicine, and JAMA) announced that they would no longer publish results of research unless that research was registered in a public database from the start. In this way, negative results should no longer be able to disappear.
- Selection bias
- Confirmation bias
- File drawer problem
- List of bias in medical literature
- list of cognitive biases
- null hypothesis
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