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Planning falsifiable confirmatory research.

James E Kennedy1

  • 1School of Philosophy, Psychology and Language Sciences, University of Edinburgh.

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|December 12, 2024
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Summary

Falsifiable research ensures science is self-correcting by defining minimum effect sizes. This approach enhances the reliability and validity of statistical analyses in psychological research.

Area of Science:

  • Psychological research methodology
  • Scientific self-correction

Background:

  • Falsifiable research is crucial for scientific progress but not widely understood by psychologists.
  • Defining effect sizes is as vital as defining populations for robust confirmatory research.

Purpose of the Study:

  • To elucidate methods for conducting falsifiable research in psychology.
  • To emphasize the importance of specifying minimum effect sizes for meaningful scientific inquiry.

Main Methods:

  • Utilizing power curves and operating characteristics to evaluate statistical analysis performance.
  • Applying frequentist and Bayesian approaches for error rate assessment.
  • Recommending preregistration with clear criteria for hypothesis outcomes.

Main Results:

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  • Specifying a minimum effect size is essential for falsifiable research; otherwise, findings may lack predictive value.
  • Optimal power (≥.95) and good power (.90) are recommended for confirmatory studies.
  • Confidence intervals offer more informative inferences than p-values.

Conclusions:

  • Falsifiable research requires clear criteria for accepting, rejecting, or deeming hypotheses inconclusive.
  • Not all confirmatory studies necessitate falsifiability.
  • Implementing these methods improves the validity and reliability of psychological research.