Abstract

We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

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