Hypothesis test

Bayesian Power Analysis (Assurance)

Bayesian power analysis — also called assurance — is a sample size determination method that replaces the frequentist notion of power with a probability-weighted average over a prior distribution on the effect size. First formalised by Spiegelhalter and Freedman (1986) and further developed by O'Hagan, Stevens and Campbell (2005), it answers the question: given our current uncertainty about the true effect, what sample size gives us a high overall probability of obtaining a statistically significant result?

Apply with StatMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. O'Hagan, A., Stevens, J.W. & Campbell, M.J. (2005). Assurance in Clinical Trial Design. Pharmaceutical Statistics, 4(3), 187–201. DOI: 10.1002/pst.175
  2. Spiegelhalter, D.J. & Freedman, L.S. (1986). A Predictive Approach to Selecting the Size of a Clinical Trial, Based on Subjective Clinical Opinion. Statistics in Medicine, 5(1), 1–13. DOI: 10.1002/sim.4780050103

Related methods

Referenced by

ScholarGateBayesian Power Analysis (Bayesian Power Analysis (Assurance / Bayesian Sample Size Determination)). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/bayesian-power-analysis