Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording
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{"title"=>"Evidence of experimental bias in the life sciences: Why we need blind data recording", "type"=>"journal", "authors"=>[{"first_name"=>"Luke", "last_name"=>"Holman", "scopus_author_id"=>"23501824500"}, {"first_name"=>"Megan L.", "last_name"=>"Head", "scopus_author_id"=>"8297849100"}, {"first_name"=>"Robert", "last_name"=>"Lanfear", "scopus_author_id"=>"25228756200"}, {"first_name"=>"Michael D.", "last_name"=>"Jennions", "scopus_author_id"=>"7004123448"}], "year"=>2015, "source"=>"PLoS Biology", "identifiers"=>{"doi"=>"10.1371/journal.pbio.1002190", "sgr"=>"84938709675", "isbn"=>"1545-7885 (Electronic)\\r1544-9173 (Linking)", "pmid"=>"26154287", "issn"=>"15457885", "scopus"=>"2-s2.0-84938709675", "pui"=>"605486414"}, "id"=>"ed3cf2df-0a8e-38f3-8865-f6ea71df118a", "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.", "link"=>"http://www.mendeley.com/research/evidence-experimental-bias-life-sciences-we-need-blind-data-recording", "reader_count"=>157, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>39, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>40, "Student > Postgraduate"=>3, "Student > Master"=>26, "Other"=>3, "Student > Bachelor"=>17, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>2, "Professor"=>10}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>39, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>40, "Student > Postgraduate"=>3, "Student > Master"=>26, "Other"=>3, "Student > Bachelor"=>17, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>2, "Professor"=>10}, "reader_count_by_subject_area"=>{"Unspecified"=>12, "Agricultural and Biological Sciences"=>72, "Philosophy"=>2, "Business, Management and Accounting"=>3, "Chemistry"=>2, "Computer Science"=>1, "Engineering"=>1, "Environmental Science"=>6, "Biochemistry, Genetics and Molecular Biology"=>7, "Nursing and Health Professions"=>2, "Mathematics"=>4, "Medicine and Dentistry"=>19, "Neuroscience"=>3, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Sports and Recreations"=>1, "Physics and Astronomy"=>1, "Psychology"=>13, "Social Sciences"=>2, "Immunology and Microbiology"=>3, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>19}, "Social Sciences"=>{"Social Sciences"=>2}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>13}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>12}, "Environmental Science"=>{"Environmental Science"=>6}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Engineering"=>{"Engineering"=>1}, "Chemistry"=>{"Chemistry"=>2}, "Neuroscience"=>{"Neuroscience"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>72}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Philosophy"=>{"Philosophy"=>2}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "Colombia"=>1, "Hungary"=>2, "United States"=>2, "Japan"=>1, "United Kingdom"=>3, "Portugal"=>2, "Switzerland"=>2, "Spain"=>1, "Canada"=>1, "Netherlands"=>1, "Sweden"=>2, "Austria"=>1, "Serbia and Montenegro"=>1, "Brazil"=>1, "France"=>1, "Nigeria"=>1, "Germany"=>6}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2167574"], "description"=>"<p>Note that the predictor and response variables were rescaled to have a mean of 0 and standard deviation of 0.5 prior to running the model [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002190#pbio.1002190.ref037\" target=\"_blank\">37</a>]. The effects of each FoR category are shown relative to the reference level “Agricultural and Veterinary Sciences.” The 95% CIs for each parameter were estimated as ±1.96 * SE.</p>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477339, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002190.t002", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_a_generalized_linear_model_with_the_proportion_of_significant_p_values_in_each_paper_as_the_response_variable_and_binomial_errors_/1477339", "title"=>"Results of a generalized linear model with the proportion of significant <i>p</i>-values in each paper as the response variable and binomial errors.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-08 03:16:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167573"], "description"=>"<p>Note that the predictor and response variables were rescaled to have a mean of 0 and standard deviation of 0.5 prior to running the models [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002190#pbio.1002190.ref037\" target=\"_blank\">37</a>]. The FoR category × Blindness interaction was not among the top models, indicating it had no detectable effect on z score. The effects of each FoR category are shown relative to the reference level “Agricultural and veterinary sciences.” The Importance column gives the summed Akaike weights of all the models containing the focal predictor; high importance shows that a parameter was present in many of the best models, and was thus a good predictor of z scores relative to the other measured variables.</p>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477338, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002190.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_each_parameter_on_z_scores_as_estimated_by_model_averaging_of_the_top_four_models_in_the_set_those_with_an_Akaike_weight_gt_0_05_/1477338", "title"=>"Effect of each parameter on z scores, as estimated by model averaging of the top four models in the set (those with an Akaike weight > 0.05).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-08 03:16:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167576", "https://ndownloader.figshare.com/files/2167577", "https://ndownloader.figshare.com/files/2167578", "https://ndownloader.figshare.com/files/2167579", "https://ndownloader.figshare.com/files/2167580", "https://ndownloader.figshare.com/files/2167581"], "description"=>"<div><p>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 <i>p</i>-values. We discuss methods to minimize bias and urge researchers, editors, and peer reviewers to keep blind protocols in mind.</p></div>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477341, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1002190.s001", "https://dx.doi.org/10.1371/journal.pbio.1002190.s002", "https://dx.doi.org/10.1371/journal.pbio.1002190.s003", "https://dx.doi.org/10.1371/journal.pbio.1002190.s004", "https://dx.doi.org/10.1371/journal.pbio.1002190.s005", "https://dx.doi.org/10.1371/journal.pbio.1002190.s006"], "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evidence_of_Experimental_Bias_in_the_Life_Sciences_Why_We_Need_Blind_Data_Recording_/1477341", "title"=>"Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-07-08 03:16:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167572"], "description"=>"<p>The numbers give the sample size (number of papers) and the percentage of papers that were blind for this dataset (note the higher sample size relative to <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002190#pbio.1002190.g002\" target=\"_blank\">Fig 2</a>). The bottom-right figure shows the median proportion of significant <i>p</i>-value papers (and the interquartile range) in each FoR category for blind and nonblind papers.</p>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477337, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002190.g003", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Density_plots_showing_the_distribution_of_the_proportion_of_significant_p_values_per_paper_i_e_the_number_of_p_values_p_values_in_putatively_experimental_blind_and_nonblind_papers_/1477337", "title"=>"Density plots showing the distribution of the proportion of significant <i>p</i>-values per paper (i.e., the number of <i>p</i>-values <0.05, divided by the total number of <i>p</i>-values) in putatively experimental blind and nonblind papers.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:16:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167570"], "description"=>"<p>The thin lines show individual pairs, while the thick line shows the average effect size for each study type. The size of the dots is inversely proportional to the variance of the effect size, such that larger dots indicate more precise estimates. For clarity, two unusually large effect sizes are off the scale (dotted lines: <i>g</i> = 18.0 and 9.1).</p>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477335, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002190.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Nonblind_studies_had_higher_effect_sizes_than_their_paired_blind_studies_on_average_n_83_pairs_/1477335", "title"=>"Nonblind studies had higher effect sizes than their paired blind studies, on average (<i>n</i> = 83 pairs).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:16:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167571"], "description"=>"<p>The dotted line shows z = 1.96 (z scores above this line are “significant” at α = 0.05), and the numbers give the sample size (number of papers) and the percentage of papers that were blind for this dataset. The bottom-right figure shows the median z score (and the interquartile range) in each FoR category for blind and nonblind papers.</p>", "links"=>[], "tags"=>["life sciences", "literature review", "researcher", "Blind Data Recording Observer bias", "text mining", "treatment group", "experimenter", "Experimental Bias", "nonblind studies", "peer reviewers", "effect sizes"], "article_id"=>1477336, "categories"=>["Biological Sciences"], "users"=>["Luke Holman", "Megan L. Head", "Robert Lanfear", "Michael D. Jennions"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002190.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Density_plots_showing_the_distribution_of_z_scores_taken_from_putatively_experimental_blind_and_nonblind_papers_/1477336", "title"=>"Density plots showing the distribution of z scores taken from putatively experimental blind and nonblind papers.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:16:53"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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