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Attributable fraction functions for censored event times

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  • Li Chen
  • D. Y. Lin
  • Donglin Zeng

Abstract

Attributable fractions are commonly used to measure the impact of risk factors on disease incidence in the population. These static measures can be extended to functions of time when the time to disease occurrence or event time is of interest. The present paper deals with nonparametric and semiparametric estimation of attributable fraction functions for cohort studies with potentially censored event time data. The semiparametric models include the familiar proportional hazards model and a broad class of transformation models. The proposed estimators are shown to be consistent, asymptotically normal and asymptotically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. A cardiovascular health study is provided. Connections to causal inference are discussed. Copyright 2010, Oxford University Press.

Suggested Citation

  • Li Chen & D. Y. Lin & Donglin Zeng, 2010. "Attributable fraction functions for censored event times," Biometrika, Biometrika Trust, vol. 97(3), pages 713-726.
    • Handle: RePEc:oup:biomet:v:97:y:2010:i:3:p:713-726
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    File URL: http://hdl.handle.net/10.1093/biomet/asq023
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    Citations

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    Cited by:

    1. Torben Martinussen & Christian Bressen Pipper, 2014. "Estimation of Causal Odds of Concordance using the Aalen Additive Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 141-151, March.
    2. Wei Zhao & Ying Qing Chen & Li Hsu, 2017. "On estimation of time-dependent attributable fraction from population-based case-control studies," Biometrics, The International Biometric Society, vol. 73(3), pages 866-875, September.
    3. García, A., 2016. "Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes," Documentos de Trabajo 14186, Universidad del Rosario.
    4. Yixin Wang & Ying Qing Chen, 2019. "Estimating Attributable Life Expectancy Under the Proportional Mean Residual Life Model," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 659-676, December.
    5. Torben Martinussen & Mats Julius Stensrud, 2023. "Estimation of separable direct and indirect effects in continuous time," Biometrics, The International Biometric Society, vol. 79(1), pages 127-139, March.
    6. Liliana Andriano & Christiaan W. S. Monden, 2019. "The Causal Effect of Maternal Education on Child Mortality: Evidence From a Quasi-Experiment in Malawi and Uganda," Demography, Springer;Population Association of America (PAA), vol. 56(5), pages 1765-1790, October.
    7. 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.

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