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Estimation statistics should replace significance testing

Nature Methods volume 13, pages 108–109 (2016) Cite this article

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To the Editor:

For more than 40 years, null-hypothesis significance testing and P values have been questioned by statistical commentators, their utility criticized on philosophical and practical grounds1. Luckily, the preferred statistical methodology is accessible with modest retraining. An obstacle to the adoption of this alternative seems to be the lack of a widely used name; we suggest the term 'estimation statistics' to describe the group of methods that focus on the estimation of effect sizes (point estimates) and their confidence intervals (precision estimates). Estimation statistics offers several key benefits with respect to current methods.

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Authors and Affiliations

  1. Program in Neuroscience and Behavioral Disorders, Duke-NUS Medical School, Singapore

    Adam Claridge-Chang

  2. Institute for Molecular and Cell Biology, Singapore

    Adam Claridge-Chang

  3. Department of Physiology, National University of Singapore, Singapore

    Adam Claridge-Chang

  4. Singapore Clinical Research Institute, Singapore

    Pryseley N Assam

  5. Centre for Quantitative Medicine, Duke-NUS Graduate Medical School, Singapore

    Pryseley N Assam

Authors
  1. Adam Claridge-Chang
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  2. Pryseley N Assam
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Correspondence to Adam Claridge-Chang.

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The authors declare no competing financial interests.

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Claridge-Chang, A., Assam, P. Estimation statistics should replace significance testing. Nat Methods 13, 108–109 (2016). https://doi.org/10.1038/nmeth.3729

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