Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
P-Value, Compatibility, and S-Value Publisher



Mansournia MA1 ; Nazemipour M1 ; Etminan M2
Authors
Show Affiliations
Authors Affiliations
  1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Ophthalmology, Medicine and Pharmacology, University of British Columbia, Vancouver, Canada

Source: Global Epidemiology Published:2022


Abstract

Misinterpretations of P-values and 95% confidence intervals are ubiquitous in medical research. Specifically, the terms significance or confidence, extensively used in medical papers, ignore biases and violations of statistical assumptions and hence should be called overconfidence terms. In this paper, we present the compatibility view of P-values and confidence intervals; the P-value is interpreted as an index of compatibility between data and the model, including the test hypothesis and background assumptions, whereas a confidence interval is interpreted as the range of parameter values that are compatible with the data under background assumptions. We also suggest the use of a surprisal measure, often referred to as the S-value, a novel metric that transforms the P-value, for gauging compatibility in terms of an intuitive experiment of coin tossing. © 2022
Other Related Docs
9. Case–Control Matching on Confounders Revisited, European Journal of Epidemiology (2023)
13. Time-Fixed Vs Time-Varying Causal Diagrams for Immortal Time Bias, International Journal of Epidemiology (2022)
15. Causal Diagrams for Immortal Time Bias, International Journal of Epidemiology (2021)
22. Using Causal Diagrams for Biomedical Research, Annals of Emergency Medicine (2023)
44. Causal Methods for Observational Research: A Primer, Archives of Iranian Medicine (2018)