The Most Difference in Means: A Statistic for the Strength of Null and Near-Zero Results

  title={The Most Difference in Means: A Statistic for the Strength of Null and Near-Zero Results},
  author={Bruce A. Corliss and Taylor R. Brown and Ting Zhang and Kevin A. Janes and Heman Shakeri and Philip E. Bourne},
  journal={SSRN Electronic Journal},
: Statistical insignificance does not suggest the absence of effect, yet scientists must often use null results as evidence of negligible (near-zero) effect size to falsify scientific hypotheses. Doing so must assess a result’s null strength, defined as the evidence for a negligible effect size. Such an assessment would differentiate high null strength results that suggest a negligible effect size from low null strength results that suggest a broad range of potential effect sizes. We propose… 

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