Sequential monitoring of clinical trials: the role of information and Brownian motion.
Sequential monitoring has been a topic of major interest in clinical trials methodology over the past two decades. This paper presents a unified conceptual framework for sequential monitoring that covers a wide variety of monitoring procedures in a wide variety of clinical trial settings. The central elements of this framework consist of a suitable concept of statistical information and a scheme for using this concept as a basis for summarizing the accumulating results of a trial in a standardized form, through a stochastic process that can be shown to approximate classical Brownian motion. The ideas are developed in a simple step-by-step fashion and illustrated by several practical examples.
Department of Statistics/Computer and Information Systems, George Washington University, Washington, D.C. 20052.
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D055592:Biophysical Phenomena; D001703:Biophysics; D002985:Clinical Protocols; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D016016:Proportional Hazards Models; D011897:Random Allocation; D012107:Research Design; D013269:Stochastic Processes; D015996:Survival Rate; D013997:Time Factors