IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v67y2011i2p331-343.html
   My bibliography  Save this article

Unbiased and Locally Efficient Estimation of Genetic Effect on Quantitative Trait in the Presence of Population Admixture

Author

Listed:
  • Yuanjia Wang
  • Qiong Yang
  • Daniel Rabinowitz

Abstract

No abstract is available for this item.

Suggested Citation

  • Yuanjia Wang & Qiong Yang & Daniel Rabinowitz, 2011. "Unbiased and Locally Efficient Estimation of Genetic Effect on Quantitative Trait in the Presence of Population Admixture," Biometrics, The International Biometric Society, vol. 67(2), pages 331-343, June.
  • Handle: RePEc:bla:biomet:v:67:y:2011:i:2:p:331-343
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01454.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Andrew S. Allen & Glen A. Satten & Anastasios A. Tsiatis, 2005. "Locally-efficient robust estimation of haplotype-disease association in family-based studies," Biometrika, Biometrika Trust, vol. 92(3), pages 559-571, September.
    2. Alice S. Whittemore, 2004. "Estimating genetic association parameters from family data," Biometrika, Biometrika Trust, vol. 91(1), pages 219-225, March.
    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. Stijn Vansteelandt & Dawn L. DeMeo & Jessica Lasky-Su & Jordan W. Smoller & Amy J. Murphy & Matt McQueen & Kady Schneiter & Juan C. Celedon & Scott T. Weiss & Edwin K. Silverman & Christoph Lange, 2008. "Testing and Estimating Gene–Environment Interactions in Family-Based Association Studies," Biometrics, The International Biometric Society, vol. 64(2), pages 458-467, June.
    2. Bo Zhang & Eric J. Tchetgen Tchetgen, 2022. "A semi‐parametric approach to model‐based sensitivity analysis in observational studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 668-691, December.

    More about this item

    Statistics

    Access and download statistics

    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:bla:biomet:v:67:y:2011:i:2:p:331-343. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.