IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v81y2011i7p807-812.html
   My bibliography  Save this article

Variance computations for functionals of absolute risk estimates

Author

Listed:
  • Pfeiffer, R.M.
  • Petracci, E.

Abstract

We present a simple influence function based approach for computing the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Suggested Citation

  • Pfeiffer, R.M. & Petracci, E., 2011. "Variance computations for functionals of absolute risk estimates," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 807-812, July.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:7:p:807-812
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(11)00040-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Barry I. Graubard & Thomas R. Fears, 2005. "Standard Errors for Attributable Risk for Simple and Complex Sample Designs," Biometrics, The International Biometric Society, vol. 61(3), pages 847-855, September.
    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. 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.
    2. Cox, Christopher & Li, Xiuhong, 2012. "Model-based estimation of the attributable risk: A loglinear approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4180-4189.
    3. Lola Etievant & Mitchell H. Gail, 2024. "Cox model inference for relative hazard and pure risk from stratified weight-calibrated case-cohort data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(3), pages 572-599, July.
    4. Yang Liu & Brenda O. Hoppe & Matteo Convertino, 2018. "Threshold Evaluation of Emergency Risk Communication for Health Risks Related to Hazardous Ambient Temperature," Risk Analysis, John Wiley & Sons, vol. 38(10), pages 2208-2221, October.
    5. Kovalchik, Stephanie & Varadhan, Ravi, 2013. "Fitting Additive Binomial Regression Models with the R Package blm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i01).
    6. Jason Brinkley & Anastasios Tsiatis & Kevin J. Anstrom, 2010. "A Generalized Estimator of the Attributable Benefit of an Optimal Treatment Regime," Biometrics, The International Biometric Society, vol. 66(2), pages 512-522, June.

    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:eee:stapro:v:81:y:2011:i:7:p:807-812. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.