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A causal proportional hazards estimator under homogeneous or heterogeneous selection in an IV setting

Author

Listed:
  • Ditte Nørbo Sørensen

    (University of Copenhagen)

  • Torben Martinussen

    (University of Copenhagen)

  • Eric Tchetgen Tchetgen

    (Wharton, University of Pennsylvania)

Abstract

In this paper we present a framework to do estimation in a structural Cox model when there may be unobserved confounding. The model is phrased in terms of a selection bias function and a baseline model that describes how covariates affect the survival time in a scenario without exposure. In this way model congeniality is ensured. The method uses an instrumental variable. Interestingly, the formulated model turns out to have similarities to the so-called Cox–Aalen survival model for the observed data. We exploit this to enhance estimation of the unknown parameters. This also allows us to derive large sample properties of the proposed estimator.

Suggested Citation

  • Ditte Nørbo Sørensen & Torben Martinussen & Eric Tchetgen Tchetgen, 2019. "A causal proportional hazards estimator under homogeneous or heterogeneous selection in an IV setting," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 639-659, October.
    • Handle: RePEc:spr:lifeda:v:25:y:2019:i:4:d:10.1007_s10985-019-09476-y
    DOI: 10.1007/s10985-019-09476-y
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    References listed on IDEAS

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    Cited by:

    1. Linbo Wang & Eric Tchetgen Tchetgen & Torben Martinussen & Stijn Vansteelandt, 2023. "Instrumental variable estimation of the causal hazard ratio," Biometrics, The International Biometric Society, vol. 79(2), pages 539-550, June.

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