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Type I Error Rates are Not Usually Inflated

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  • Rubin, Mark

    (Durham University)

Abstract

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin by introducing the concept of Type I error rates and distinguishing between statistical errors and theoretical errors. I then illustrate my argument with respect to model misspecification, multiple testing, selective inference, forking paths, exploratory analyses, p-hacking, optional stopping, double dipping, and HARKing. In each case, I demonstrate that relevant Type I error rates are not usually inflated above their nominal level, and in the rare cases that they are, the inflation is easily identified and resolved. I conclude that the replication crisis may be explained, at least in part, by researchers’ misinterpretation of statistical errors and their underestimation of theoretical errors.

Suggested Citation

  • Rubin, Mark, 2024. "Type I Error Rates are Not Usually Inflated," MetaArXiv 3kv2b_v1, Center for Open Science.
  • Handle: RePEc:osf:metaar:3kv2b_v1
    DOI: 10.31219/osf.io/3kv2b_v1
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