Predictively Consistent Prior Effective Sample Sizes

by   Beat Neuenschwander, et al.

Determining the sample size of an experiment can be challenging, even more so when incorporating external information via a prior distribution. Such information is increasingly used to reduce the size of the control group in randomized clinical trials. Knowing the amount of prior information, expressed as an equivalent prior effective sample size (ESS), clearly facilitates trial designs. Various methods to obtain a prior's ESS have been proposed recently. They have been justified by the fact that they give the standard ESS for one-parameter exponential families. However, despite being based on similar information-based metrics, they may lead to surprisingly different ESS for non-conjugate settings, which complicates many designs with prior information. We show that current methods fail a basic predictive consistency criterion, which requires the expected posterior-predictive ESS for a sample of size N to be the sum of the prior ESS and N. The expected local-information-ratio ESS is introduced and shown to be predictively consistent. It corrects the ESS of current methods, as shown for normally distributed data with a heavy-tailed Student-t prior and exponential data with a generalized Gamma prior. Finally, two applications are discussed: the prior ESS for the control group derived from historical data, and the posterior ESS for hierarchical subgroup analyses.


page 1

page 2

page 3

page 4


Conditional Power and Friends: The Why and How of (Un)planned, Unblinded Sample Size Recalculations in Confirmatory Trials

Adapting the final sample size of a trial to the evidence accruing durin...

A Conservative Approach to Leveraging External Evidence for Effective Clinical Trial Design

Mainstream methods for clinical trial design do not yet use prior probab...

Hybrid sample size calculations for cluster randomised trials using assurance

Sample size determination for cluster randomised trials (CRTs) is challe...

Objective Bayesian approach to the Jeffreys-Lindley paradox

We consider the Jeffreys-Lindley paradox from an objective Bayesian pers...

Posterior Probabilities: Nonmonotonicity, Asymptotic Rates, Log-Concavity, and Turán's Inequality

In the standard Bayesian framework data are assumed to be generated by a...

Bayesian sample size determination for diagnostic accuracy studies

The development of a new diagnostic test ideally follows a sequence of s...

Please sign up or login with your details

Forgot password? Click here to reset