Understanding Cherry-Picking in Research: Practices and Consequences
Cherry-picking in research involves selectively reporting variables, conditions, or treatments with high p-values, omitting non-significant results, and claiming completeness when other models were also tested. This unethical practice skews meta-analyses, impedes interpretation, leads to redundant investigations, and deprives readers of crucial information.
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Questionable Research Practices Part 1: Cherry picking 1
Cherry picking Failing to report variables, conditions, or treatments that had relatively high p-values. 2 Cherry picking by barnimages.com, CC BY 2.0
Cherry picking n = 573 Ecologists, 299 Evolutionary biologists 1. Not reporting studies or variables that failed to reach statistical significance (e.g. p 0.05) or some other desired statistical threshold. 2. Not reporting covariates that failed to reach statistical significance (e.g. p 0.05) or some other desired statistical threshold. 4. Reporting a set of statistical models as the complete tested set when other candidate models were also tested. 3
Cherry picking Reported having done at least once 4
Cherry picking Reported having done at least once 5
Cherry picking - consequences Impedes interpretation Non-significant results are important Readers lack the information Skews meta-analyses Leads to redundant investigation Unethical 7
