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Investigating Time Dependence in Cox's Proportional Hazards Model

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  • A. N. Pettitt
  • I. Bin Daud

Abstract

We consider the investigation of time dependence in Cox's proportional hazards model using the residuals of Schoenfeld. For data analysis and model development we consider smoothing these residuals to consider time‐dependent effects. A model which considers time‐dependent modulation of the linear predictor is introduced and suggested for use. The techniques are illustrated using simulated data and data concerning the failure response, measured as distance travelled, of turbochargers on railway carriages. For the latter case, a ‘time‘‐dependent proportional hazards model of this type is suggested by smoothing the residuals and it is shown to give an improved fit to the data.

Suggested Citation

  • A. N. Pettitt & I. Bin Daud, 1990. "Investigating Time Dependence in Cox's Proportional Hazards Model," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(3), pages 313-329, November.
    • Handle: RePEc:bla:jorssc:v:39:y:1990:i:3:p:313-329
    DOI: 10.2307/2347382
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    Cited by:

    1. Laudicella, Mauro & Siciliani, Luigi & Cookson, Richard, 2012. "Waiting times and socioeconomic status: Evidence from England," Social Science & Medicine, Elsevier, vol. 74(9), pages 1331-1341.
    2. Wei Pan, 2001. "A Multiple Imputation Approach to Regression Analysis for Doubly Censored Data with Application to AIDS Studies," Biometrics, The International Biometric Society, vol. 57(4), pages 1245-1250, December.
    3. Ronghui Xu & Sudeshna Adak, 2002. "Survival Analysis with Time-Varying Regression Effects Using a Tree-Based Approach," Biometrics, The International Biometric Society, vol. 58(2), pages 305-315, June.
    4. Rezgar Zaki & Abbas Barabadi & Javad Barabady & Ali Nouri Qarahasanlou, 2022. "Observed and unobserved heterogeneity in failure data analysis," Journal of Risk and Reliability, , vol. 236(1), pages 194-207, February.

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