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Biometrika 1996 83(4):779-789; doi:10.1093/biomet/83.4.779
© 1996 by Biometrika Trust
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Repeated significance testing in longitudinal clinical trials

SANDRA J. LEE, KYUNGMANN KIM and ANASTASIOS A. TSIATIS

Division of Biostatistics, Dana-Farber Cancer Institute Boston, Massachusetts 02115, U.S.A.
University of Michigan Comprehensive Cancer Center Ann Arbor, Michigan 48109, U.S.A.
Department of Biostatistics, Harvard School of Public Health Boston, Massachusetts 02115, U.S.A.

When longitudinal clinical trials are monitored, multiplicity from repeated significance testing as well as from repeated measures has to be accounted for properly to control the overall type I error. This often involves a multidimensional integration procedure to compute group sequential boundaries. We establish an independent increments structure of sequentially computed test statistics based on the generalised estimating equations of Liang & Zeger (1986) for longitudinal data. This simplifies the computational procedure for group sequential boundaries to one involving recursive one-dimensional integrations and allows the use of standard methodology for group sequential tests. We also apply the error spending function approach of Lan & DeMets (1983) by defining information fraction in this setting.

Key Words: Error spending function • Generalised estimating equation • Group sequential • Independent increments • Repeated measures • Score test • Wald test


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B. Spiessens, E. Lesaffre, G. Verbeke, K. Kim, and D. L DeMets
An overview of group sequential methods in longitudinal clinical trials
Statistical Methods in Medical Research, October 1, 2000; 9(5): 497 - 515.
[Abstract] [PDF]


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