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Updated: May 7, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Do baseline P-values follow a uniform distribution in randomised trials?

Martin Bland1

  • 1Department of Health Sciences, University of York, York, North Yorkshire, United Kingdom.

Plos One
|October 8, 2013
PubMed
Summary

P-values should follow a Uniform distribution for valid randomization, but simulations show this is only true for independent, normally distributed data. This method is unreliable for Lognormal data, correlated variables, or binary data.

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Area of Science:

  • Statistical methodology
  • Clinical trial design

Background:

  • A theory suggests P-values should uniformly distribute under a true null hypothesis.
  • This property has been proposed as a method to validate randomization in clinical trials.

Purpose of the Study:

  • To empirically test the Uniform distribution theory of P-values across various statistical tests and data types.
  • To assess the reliability of using P-value distribution as a check for valid randomization.

Main Methods:

  • Simulations were conducted for two-sample t-tests using Normal and Lognormal distributions.
  • Tests included independent and non-independent (correlated) samples.
  • Chi-squared and Fisher's exact tests were evaluated for binary data in small and large samples.

Main Results:

  • P-value distribution closely approximated Uniform for independent Normal data t-tests.
  • Lognormal data, correlated variables, and binary data (chi-squared, Fisher's exact) showed significant deviations from Uniform distribution.
  • Uneven P-value distributions and poor fits to Uniform were observed, especially with large binary samples.

Conclusions:

  • The Uniform P-value distribution theory holds only for independent, Normal data, not for Lognormal, correlated, or binary data.
  • The proposed method of checking randomization validity using P-value distribution is unreliable across diverse data types and test scenarios.