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Comparisons of Test Statistics Arising from Marginal Analyses of Multivariate Survival Data

In: Probability, Statistics and Modelling in Public Health

Author

Listed:
  • Qian H. Li

    (Food and Drug Administration, Center for Drug and Evaluation Research, HFD-705)

  • Stephen W. Lagakos

    (Harvard School of Public Health, Department of Biostatistics)

Abstract

Summary We investigate the properties of several statistical tests for comparing treatment groups with respect to multivariate survival data, based on the marginal analysis approach introduced by Wei, Lin and Weissfeld [WLW89]. We consider two types of directional tests, based on a constrained maximization and on linear combinations of the unconstrained maximizer of the working likelihood function, and the omnibus test arising from the same working likelihood. The directional tests are members of a larger class of tests, from which an asymptotically optimal test can be found. We compare the asymptotic powers of the tests under general contiguous alternatives for a variety of settings, and also consider the choice of the number of survival times to include in the multivariate outcome. We illustrate the results with two simulations and with the results from a clinical trial examining recurring opportunistic infections in persons with HIV.

Suggested Citation

  • Qian H. Li & Stephen W. Lagakos, 2006. "Comparisons of Test Statistics Arising from Marginal Analyses of Multivariate Survival Data," Springer Books, in: Mikhail Nikulin & Daniel Commenges & Catherine Huber (ed.), Probability, Statistics and Modelling in Public Health, pages 299-318, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-26023-5_20
    DOI: 10.1007/0-387-26023-4_20
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