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Funding bias, also known as sponsorship bias, funding outcome bias, funding publication bias, and funding effect, is a tendency of a scientific study to support the interests of the study's financial sponsor. This phenomenon is recognized sufficiently that researchers undertake studies to examine bias in past published studies.
These supplements are often subsidized by an external sponsor with a financial interest in the outcome of research in that field; for instance, a drug manufacturer or food industry group. Such supplements can have guest editors, [ 2 ] are often not peer-reviewed to the same standard as the journal itself, and are more likely to use promotional ...
Three percent of the 3,475 research institutions that report to the US Department of Health and Human Services' Office of Research Integrity, indicate some form of scientific misconduct. [7] However the ORI will only investigate allegations of impropriety where research was funded by federal grants.
Publishing only results that show a significant finding disturbs the balance of findings in favor of positive results. [1] The study of publication bias is an important topic in metascience . Despite similar quality of execution and design , [ 2 ] papers with statistically significant results are three times more likely to be published than ...
The publication or nonpublication of research findings, depending on the nature and direction of the results. Although medical writers have acknowledged the problem of reporting biases for over a century, [12] it was not until the second half of the 20th century that researchers began to investigate the sources and size of the problem of reporting biases.
"Why Most Published Research Findings Are False" is a 2005 essay written by John Ioannidis, a professor at the Stanford School of Medicine, and published in PLOS Medicine. [1] It is considered foundational to the field of metascience .
Ioannidis describes what he views as some of the problems and calls for reform, characterizing certain points for medical research to be useful again; one example he makes is the need for medicine to be patient-centered (e.g. in the form of the Patient-Centered Outcomes Research Institute) instead of the current practice to mainly take care of ...
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [1]