Boundary Scales in RCTdesign

Many authors make distinctions between clinical trial designs derived using “group sequential designs” (e.g., O’Brien-Fleming or Pocock designs), “error spending functions” (e.g., Lan & DeMets or Hwang, Shih, & DeCani), “stochastic curtailment” (e.g., conditional power or Bayesian predictive power), and “Bayesian designs” based on posterior probabilities. However, in RCTdesign we regard these as “distinctions without differences”. In fact, every sequential stopping rule can be expressed in each of those boundary scales. In this tutorial, we demonstrate the way the various boundary scales are speciified in RCTdesign, in order that the user can evaluate the appropriateness of a particular sequential sampling scheme on the scales that are of greatest interest in a particular application. Alternative tutorials discuss the relative merits of particular boundary scales in greater detail.