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Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations

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Survival Analysis: State of the Art

Part of the book series: Nato Science ((NSSE,volume 211))

Abstract

The Cox regression model has been used extensively to analyze survival data. For data that consist of large numbers of small groups of correlated failure time observations, we show that the standard maximum partial likelihood estimate of the regression coefficient in the Cox model is still consistent and asymptotically normal. However, the corresponding standard variance-covariance estimate may no longer be valid due to the dependence among members in the groups. In this article, a correct variance-covariance estimate that takes account of the intra-group correlation is proposed. Power comparisons are performed to show the advantage of the new proposal. Examples are provided for illustration.

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© 1992 Springer Science+Business Media Dordrecht

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Lee, E.W., Wei, L.J., Amato, D.A., Leurgans, S. (1992). Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations. In: Klein, J.P., Goel, P.K. (eds) Survival Analysis: State of the Art. Nato Science, vol 211. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7983-4_14

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  • DOI: https://doi.org/10.1007/978-94-015-7983-4_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4133-3

  • Online ISBN: 978-94-015-7983-4

  • eBook Packages: Springer Book Archive

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