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- W2904294379 abstract "Increasingly complex statistical models are being used for the analysis of biological data. Recent commentary has focused on the ability to compute the same outcome for a given dataset (reproducibility). We argue that a reproducible statistical analysis is not necessarily valid because of unique patterns of nonindependence in every biological dataset. We advocate that analyses should be evaluated with known-truth simulations that capture biological reality, a process we call “analysis validation.” We review the process of validation and suggest criteria that a validation project should meet. We find that different fields of science have historically failed to meet all criteria, and we suggest ways to implement meaningful validation in training and practice." @default.
- W2904294379 created "2018-12-22" @default.
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- W2904294379 date "2018-12-10" @default.
- W2904294379 modified "2023-09-27" @default.
- W2904294379 title "Analysis validation has been neglected in the Age of Reproducibility" @default.
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- W2904294379 doi "https://doi.org/10.1371/journal.pbio.3000070" @default.
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