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Some comments on frequently used multiple endpoint adjustment methods in clinical trials
Statistics in Medicine · 1997 · Vol. 16(22) · pp. 2529–2542
Abdul J. Sankoh✉(Center for Drug Evaluation and Research)Mohammad F. Huque(Center for Drug Evaluation and Research)S. D. Dubey(Center for Drug Evaluation and Research)
Abstract
Confirmatory clinical trials often classify clinical response variables into primary and secondary endpoints. The presence of two or more primary endpoints in a clinical trial usually means that some adjustments of the observed p-values for multiplicity of tests may be required for the control of the type I error rate. In this paper, we discuss statistical concerns associated with some commonly used multiple endpoint adjustment procedures. We also present limited Monte Carlo simulation results to demonstrate the performance of selected p-value-based methods in protecting the type I error rate.
Statistical Methods in Clinical TrialsStatistical Methods and InferenceOptimal Experimental Design MethodsType I and type II errorsClinical endpointClinical trialStatisticsMonte Carlo methodComputer scienceEconometricsMedicineMathematicsInternal medicine
MeSH terms
AlgorithmsClinical Trials as TopicComputer SimulationData Interpretation, StatisticalHumansMonte Carlo MethodStatistics as Topic
Citations
803
FWCI
2.74
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