Better Accuracy for Better Science.. Through Random Conclusions

Clintin P. Davis-Stober, Jason Dana, David Kellen, Sara D. McMullin, Wes Bonifay

Research output: Contribution to journalArticlepeer-review

Abstract

Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable from flipping a coin to determine the direction of treatment effects. We use this idea of random conclusions to establish a baseline for interpreting effect-size estimates, in turn producing more stringent thresholds for hypothesis testing and for statistical-power calculations. An examination of recent meta-analyses in psychology, neuroscience, and medicine confirms that, even if all considered effects are real, results involving small effects are indeed indistinguishable from random conclusions.

Original languageEnglish (US)
JournalPerspectives on Psychological Science
DOIs
StateAccepted/In press - 2023

Keywords

  • benchmarks
  • estimation
  • hypothesis testing
  • random conclusions
  • t tests

ASJC Scopus subject areas

  • Psychology(all)

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