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bioRxiv · 10.1101/2025.04.06.646254

A global P-Process map to avoid P-value abuse

Xu, J.·Wei, S.·Tao, J.·Sun, C.·Chen, H.·Duan, L.·Shang, Z.·Lyu, W.·Lyu, H.·Zhang, M.·Jiang, Y.
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Abstract

P-abuse is serious in difference identification analysis of data. How to avoid P-abuse is a huge challenge. Here, we evolve P-value (a single value) to P-Process (a global landscape of P-values under different sample size) to help researchers correctly recognize and use p-value. We observed -ln(P-Process) after rotation has very similar morphology with Wiener Process (or Brownian motion). Based on this property, for any sample size, we estimated the 95% fluctuation range of P-value and further estimated how many samples (N95()) could make sure 95% of P-values less than the given significant level . Tests proved that the estimation obtains a good performance with only a small number of samples in each group. For broader accessibility, a free web-service, P-Process Map, is available online to show the whole landscape of P-Process. At the end of the article, we explained 10 of the most typical P-abuse problems which can be easily voided by using P-Process. This "rethinking" of P-value from a higher position, which is profoundly different from the way we have seen this for the past century, would yield a new era - 2P era in which hypothesis testing is strongly required to evolve from P-value to P-Process.

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Xu, J., Wei, S., Tao, J., Sun, C., Chen, H., Duan, L., Shang, Z., Lyu, W., Lyu, H., Zhang, M., Jiang, Y.. 2025-04-09. A global P-Process map to avoid P-value abuse. https://doi.org/10.1101/2025.04.06.646254

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