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CP function: an alpha spending function based on conditional power
Author(s) -
Jiang Zhiwei,
Wang Ling,
Li Chanjuan,
Xia Jielai,
Wang William
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6279
Subject(s) - function (biology) , conditional expectation , mathematics , power function , type i and type ii errors , mathematical optimization , alpha (finance) , type (biology) , computer science , statistics , mathematical analysis , ecology , construct validity , evolutionary biology , biology , psychometrics
Alpha spending function and stochastic curtailment are two frequently used methods in group sequential design. In the stochastic curtailment approach, the actual type I error probability cannot be well controlled within the specified significance level. But conditional power (CP) in stochastic curtailment is easier to be accepted and understood by clinicians. In this paper, we develop a spending function based on the concept of conditional power, named CP function, which combines desirable features of alpha spending and stochastic curtailment. Like other two‐parameter functions, CP function is flexible to fit the needs of the trial. A simulation study is conducted to explore the choice of CP boundary in CP function that maximizes the trial power. It is equivalent to, even better than, classical Pocock, O'Brien–Fleming, and quadratic spending function as long as a proper ρ 0 is given, which is pre‐specified CP threshold for efficacy. It also well controls the overall type I error type I error rate and overcomes the disadvantage of stochastic curtailment. Copyright © 2014 John Wiley & Sons, Ltd.