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Case‐Weighted Measures of Influence for Proportional Hazards Regression

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  • A. N. Pettitt
  • I. Bin Daud

Abstract

In this paper we consider the development of diagnostics and the assessment of case influence for the proportional hazards model of Cox. We critically examine various residuals which have been defined for this model and suggest that, instead of using these to assess certain model assumptions, diagnostics based on case‐weighted measures of influence should be used routinely. The ideas of Cook on local influence are applied to the proportional hazards model and useful statistics and plots are derived. We show that certain plots involving these residuals and diagnostics will in most cases be dominated by deterministic pattern and suggest their use with caution. Other plots are recommended and shown to be useful. Two data sets are considered to illustrate the techniques.

Suggested Citation

  • A. N. Pettitt & I. Bin Daud, 1989. "Case‐Weighted Measures of Influence for Proportional Hazards Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 51-67, March.
    • Handle: RePEc:bla:jorssc:v:38:y:1989:i:1:p:51-67
    DOI: 10.2307/2347680
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    Cited by:

    1. Wen Hsiang Wei & Michael R. Kosorok, 2000. "Masking Unmasked in the Proportional Hazards Model," Biometrics, The International Biometric Society, vol. 56(4), pages 991-995, December.
    2. Corette B. Parker & Elizabeth R. Belong, 2000. "A Diagnostic for Cox Regression with Discrete Failure-Time Models," Biometrics, The International Biometric Society, vol. 56(4), pages 996-1001, December.

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