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    Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording

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    83
    Author
    Holman, L; Head, ML; Lanfear, R; Jennions, MD
    Date
    2015-07-01
    Source Title
    PLoS Biology
    Publisher
    PUBLIC LIBRARY SCIENCE
    University of Melbourne Author/s
    Holman, Luke
    Affiliation
    School of BioSciences
    Metadata
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    Document Type
    Journal Article
    Citations
    Holman, 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 Status
    Open Access
    URI
    http://hdl.handle.net/11343/259205
    DOI
    10.1371/journal.pbio.1002190
    ARC Grant code
    ARC/DE140101481
    Abstract
    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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