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Better Accuracy for Better Science . . . Through Random Conclusions.

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Research with small sample sizes and subtle effects can produce results as random as a coin flip. This challenges traditional hypothesis testing and statistical power calculations, even for real effects.

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Area of Science:

  • Psychology, Neuroscience, and Medicine

Background:

  • Research with human subjects faces challenges due to limited sample sizes and small empirical effects.
  • These limitations can lead to findings that are difficult to distinguish from random chance.

Purpose of the Study:

  • To establish a baseline for interpreting effect-size estimates using the concept of random conclusions.
  • To propose more stringent thresholds for hypothesis testing and statistical-power calculations.

Main Methods:

  • Demonstrating that patterns of results from small-sample research can be indistinguishable from random outcomes.
  • Examining recent meta-analyses in psychology, neuroscience, and medicine to assess the indistinguishability of small effects.

Main Results:

  • Findings from studies with small effects are practically indistinguishable from random conclusions.
  • This indistinguishability holds true even when the underlying effects are real.

Conclusions:

  • The inherent difficulties in small-sample research necessitate a re-evaluation of statistical interpretation.
  • More rigorous standards for hypothesis testing and power calculations are required to account for the potential for random outcomes.