IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v6y2010i2n5.html
   My bibliography  Save this article

Attributable Fractions for Sufficient Cause Interactions

Author

Listed:
  • VanderWeele Tyler J

    (Harvard University)

Abstract

A number of results concerning attributable fractions for sufficient cause interactions are given. Results are given both for etiologic fractions (i.e. the proportion of the disease due to a particular sufficient cause) and for excess fractions (i.e. the proportion of disease that could be eliminated by removing a particular sufficient cause). Results are given both with and without assumptions of monotonicity. Under monotonicity assumptions, exact formulas can be given for the excess fraction. When etiologic fractions are of interest or when monotonicity assumptions do not hold for excess fractions then only lower bounds can be given. The interpretation of the results in this paper and in a proposal by Hoffmann et al. (2006) are discussed and compared. A method is described to estimate the lower bounds on attributable fractions using marginal structural models. Identification is discussed in settings in which time-dependent confounding may be present.

Suggested Citation

  • VanderWeele Tyler J, 2010. "Attributable Fractions for Sufficient Cause Interactions," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-28, February.
  • Handle: RePEc:bpj:ijbist:v:6:y:2010:i:2:n:5
    DOI: 10.2202/1557-4679.1202
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1557-4679.1202
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1557-4679.1202?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. VanderWeele Tyler J, 2010. "Epistatic Interactions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-24, January.
    2. Tyler J. Vanderweele & James M. Robins, 2008. "Empirical and counterfactual conditions for sufficient cause interactions," Biometrika, Biometrika Trust, vol. 95(1), pages 49-61.
    3. Vansteelandt, Stijn & VanderWeele, Tyler J. & Tchetgen, Eric J. & Robins, James M., 2008. "Multiply Robust Inference for Statistical Interactions," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1693-1704.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. VanderWeele Tyler J, 2010. "Epistatic Interactions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-24, January.
    2. Jui-Hsiang Lin & Wen-Chung Lee, 2015. "Testing for Mechanistic Interactions in Long-Term Follow-Up Studies," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-10, March.
    3. Ting Ye & Ashkan Ertefaie & James Flory & Sean Hennessy & Dylan S. Small, 2023. "Instrumented difference‐in‐differences," Biometrics, The International Biometric Society, vol. 79(2), pages 569-581, June.
    4. Zihuai He & Min Zhang & Seunggeun Lee & Jennifer A. Smith & Sharon L. R. Kardia & V. Diez Roux & Bhramar Mukherjee, 2017. "Set-Based Tests for the Gene–Environment Interaction in Longitudinal Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 966-978, July.
    5. VanderWeele Tyler J, 2011. "Principal Stratification -- Uses and Limitations," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-14, July.
    6. James Y. Dai & C. Jason Liang & Michael LeBlanc & Ross L. Prentice & Holly Janes, 2018. "Case†only approach to identifying markers predicting treatment effects on the relative risk scale," Biometrics, The International Biometric Society, vol. 74(2), pages 753-763, June.
    7. Ryan Sun & Raymond J. Carroll & David C. Christiani & Xihong Lin, 2018. "Testing for gene–environment interaction under exposure misspecification," Biometrics, The International Biometric Society, vol. 74(2), pages 653-662, June.
    8. Karel Vermeulen & Stijn Vansteelandt, 2015. "Bias-Reduced Doubly Robust Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1024-1036, September.
    9. Shuai Chen & Lu Tian & Tianxi Cai & Menggang Yu, 2017. "A general statistical framework for subgroup identification and comparative treatment scoring," Biometrics, The International Biometric Society, vol. 73(4), pages 1199-1209, December.
    10. Carlo Berzuini & A. Philip Dawid, 2016. "Stochastic mechanistic interaction," Biometrika, Biometrika Trust, vol. 103(1), pages 89-102.
    11. Stijn Vansteelandt & Oliver Dukes, 2022. "Assumption‐lean inference for generalised linear model parameters," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 657-685, July.
    12. Wen-Chung Lee, 2014. "Estimation of a Common Effect Parameter from Follow-Up Data When There Is No Mechanistic Interaction," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-5, January.
    13. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
    14. Peisong Han, 2016. "Combining Inverse Probability Weighting and Multiple Imputation to Improve Robustness of Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 246-260, March.
    15. Eric J. Tchetgen Tchetgen & James Robins, 2010. "The Semiparametric Case-Only Estimator," Biometrics, The International Biometric Society, vol. 66(4), pages 1138-1144, December.
    16. Zhilan Lou & Jun Shao & Menggang Yu, 2018. "Optimal treatment assignment to maximize expected outcome with multiple treatments," Biometrics, The International Biometric Society, vol. 74(2), pages 506-516, June.
    17. Tyler J. VanderWeele & Yu Chen & Habibul Ahsan, 2011. "Inference for Causal Interactions for Continuous Exposures under Dichotomization," Biometrics, The International Biometric Society, vol. 67(4), pages 1414-1421, December.
    18. Jaffer M. Zaidi & Tyler J. VanderWeele, 2021. "On the identification of individual level pleiotropic, pure direct, and principal stratum direct effects without cross world assumptions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 881-907, September.
    19. Binder Harald & Müller Tina & Schwender Holger & Golka Klaus & Steffens Michael & Hengstler Jan G. & Ickstadt Katja & Schumacher Martin, 2012. "Cluster-Localized Sparse Logistic Regression for SNP Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-31, August.
    20. Lucia Babino & Andrea Rotnitzky & James Robins, 2019. "Multiple robust estimation of marginal structural mean models for unconstrained outcomes," Biometrics, The International Biometric Society, vol. 75(1), pages 90-99, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:ijbist:v:6:y:2010:i:2:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.