Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording
Web of Science
AuthorHolman, L; Head, ML; Lanfear, R; Jennions, MD
Source TitlePLoS Biology
PublisherPUBLIC LIBRARY SCIENCE
University of Melbourne Author/sHolman, Luke
AffiliationSchool of BioSciences
Document TypeJournal Article
CitationsHolman, L., Head, M. L., Lanfear, R. & Jennions, M. D. (2015). Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording. PLOS BIOLOGY, 13 (7), https://doi.org/10.1371/journal.pbio.1002190.
Access StatusOpen Access
ARC Grant codeARC/DE140101481
Observer bias and other "experimenter effects" occur when researchers' expectations influence study outcome. These biases are strongest when researchers expect a particular result, are measuring subjective variables, and have an incentive to produce data that confirm predictions. To minimize bias, it is good practice to work "blind," meaning that experimenters are unaware of the identity or treatment group of their subjects while conducting research. Here, using text mining and a literature review, we find evidence that blind protocols are uncommon in the life sciences and that nonblind studies tend to report higher effect sizes and more significant p-values. We discuss methods to minimize bias and urge researchers, editors, and peer reviewers to keep blind protocols in mind.
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