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Efficient t0$$ {t}_0 $$‐year risk regression using the logistic model

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  • Torben Martinussen
  • Thomas Harder Scheike

Abstract

In some clinical studies patient survival beyond a specific point in time, t0$$ {t}_0 $$, say, may be of special interest as it may for instance indicate patient cure. To analyze the t0$$ {t}_0 $$‐year risk for such patients may be accomplished using logistic regression with appropriate weights (IPWCC) that may further be augmented (AIPWCC) to improve efficiency. In this paper, we derive the most efficient estimator for this problem, which is different from the AIPWCC based on the full data efficient influence function. We first give the result for a survival endpoint and then generalize to the competing risk setting. The proposed estimators superior behavior is illustrated using simulations as well as applying it to some real data concerning the survival of blood and marrow transplanted patients.

Suggested Citation

  • Torben Martinussen & Thomas Harder Scheike, 2023. "Efficient t0$$ {t}_0 $$‐year risk regression using the logistic model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(4), pages 1919-1932, December.
    • Handle: RePEc:bla:scjsta:v:50:y:2023:i:4:p:1919-1932
    DOI: 10.1111/sjos.12658
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    References listed on IDEAS

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