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Data transformation practices in biomedical sciences

Nature Methods volume 8, pages 104–105 (2011)Cite this article

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To the Editor:

In over a century since it was first introduced by William Sealy Gosset (under the pseudonym Student), the t-test has become one of the most common tests in many fields of research1 and is now a basic element in a biologist's toolkit for statistical hypothesis testing. Our screen of the first 2010 issue of medical and biological science journals with an impact factor higher than 15 revealed that in 88 of the 213 research articles, the authors had used t-tests to analyze their data ( Supplementary Methods ).

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Figure 1: Data normalization prior to applying t-test and its consequences on type I and type II error rates.

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Acknowledgements

We thank F. Riess for discussions and A. Valcu for making this work possible.

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Author notes

  1. Mihai Valcu and Cristina-Maria Valcu: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Behavioral Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany

    Mihai Valcu

  2. Department of Experimental and Molecular Pediatric Cardiology, German Heart Centre, Technical University Munich, Munich, Germany

    Cristina-Maria Valcu

Authors
  1. Mihai Valcu
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  2. Cristina-Maria Valcu
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Corresponding author

Correspondence to Cristina-Maria Valcu.

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The authors declare no competing financial interests.

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Supplementary Figures 1-3, Supplementary Methods (PDF 3056 kb)

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Valcu, M., Valcu, CM. Data transformation practices in biomedical sciences. Nat Methods 8, 104–105 (2011). https://doi.org/10.1038/nmeth0211-104

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