IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v68y2012i3p869-877.html
   My bibliography  Save this article

Semiparametric Maximum Likelihood Methods for Analyzing Genetic and Environmental Effects with Case-Control Mother–Child Pair Data

Author

Listed:
  • Jinbo Chen
  • Dongyu Lin
  • Hagit Hochner

Abstract

No abstract is available for this item.

Suggested Citation

  • Jinbo Chen & Dongyu Lin & Hagit Hochner, 2012. "Semiparametric Maximum Likelihood Methods for Analyzing Genetic and Environmental Effects with Case-Control Mother–Child Pair Data," Biometrics, The International Biometric Society, vol. 68(3), pages 869-877, September.
  • Handle: RePEc:bla:biomet:v:68:y:2012:i:3:p:869-877
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01728.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. Nilanjan Chatterjee & Raymond J. Carroll, 2005. "Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies," Biometrika, Biometrika Trust, vol. 92(2), pages 399-418, June.
    2. Chen, Yi-Hau & Chatterjee, Nilanjan & Carroll, Raymond J., 2009. "Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 220-233.
    3. Bhramar Mukherjee & Nilanjan Chatterjee, 2008. "Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency," Biometrics, The International Biometric Society, vol. 64(3), pages 685-694, September.
    4. Lin, D.Y. & Zeng, D., 2006. "Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 89-104, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Álvarez-Liébana, J. & Bosq, D. & Ruiz-Medina, M.D., 2017. "Asymptotic properties of a component-wise ARH(1) plug-in predictor," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 12-34.
    2. Nguile-Makao, Moliere & Bureau, Alexandre, 2015. "Semi-Parametric Maximum Likelihood Method for Interaction in Case-Mother Control-Mother Designs: Package SPmlficmcm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i10).

    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. Brisa N. Sánchez & Shan Kang & Bhramar Mukherjee, 2012. "A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures," Biometrics, The International Biometric Society, vol. 68(2), pages 466-476, June.
    2. Hua Yun Chen & Daniel E. Rader & Mingyao Li, 2015. "Likelihood Inferences on Semiparametric Odds Ratio Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1125-1135, September.
    3. Bhramar Mukherjee & Jaeil Ahn & Stephen B. Gruber & Malay Ghosh & Nilanjan Chatterjee, 2010. "Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis," Biometrics, The International Biometric Society, vol. 66(3), pages 934-948, September.
    4. Yulia V. Marchenko & Raymond K. Carroll & Danyu Y. Lin & Christopher I. Amos & Roberto G. Gutierrez, 2008. "Semiparametric analysis of case–control genetic data in the presence of environmental factors," Stata Journal, StataCorp LP, vol. 8(3), pages 305-333, September.
    5. Liang, Liang & Ma, Yanyuan & Carroll, Raymond J., 2019. "A semiparametric efficient estimator in case-control studies for gene–environment independent models," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 38-50.
    6. Tianying Wang & Alex Asher, 2021. "Improved Semiparametric Analysis of Polygenic Gene–Environment Interactions in Case–Control Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 386-401, December.
    7. Bhramar Mukherjee & Nilanjan Chatterjee, 2008. "Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency," Biometrics, The International Biometric Society, vol. 64(3), pages 685-694, September.
    8. Yuan Zhang & Shili Lin & Swati Biswas, 2017. "Detecting rare and common haplotype–environment interaction under uncertainty of gene–environment independence assumption," Biometrics, The International Biometric Society, vol. 73(1), pages 344-355, March.
    9. Jinbo Chen & Carmen Rodriguez, 2007. "Conditional Likelihood Methods for Haplotype-Based Association Analysis Using Matched Case–Control Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1099-1107, December.
    10. Iryna Lobach & Raymond J. Carroll & Christine Spinka & Mitchell H. Gail & Nilanjan Chatterjee, 2008. "Haplotype‐Based Regression Analysis and Inference of Case–Control Studies with Unphased Genotypes and Measurement Errors in Environmental Exposures," Biometrics, The International Biometric Society, vol. 64(3), pages 673-684, September.
    11. Hao Cheng & Ying Wei, 2018. "A fast imputation algorithm in quantile regression," Computational Statistics, Springer, vol. 33(4), pages 1589-1603, December.
    12. Summer S. Han & Philip S. Rosenberg & Nilanjan Chatterjee, 2012. "Testing for Gene--Environment and Gene--Gene Interactions Under Monotonicity Constraints," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1441-1452, December.
    13. Stephen S. M. Lee & Mehdi Soleymani, 2015. "A Simple Formula for Mixing Estimators With Different Convergence Rates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1463-1478, December.
    14. Wu Song & Yang Jie & Wu Rongling, 2010. "Mapping Quantitative Trait Loci in a Non-Equilibrium Population," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-21, August.
    15. French Benjamin & Lumley Thomas & Cappola Thomas P. & Mitra Nandita, 2012. "Non-Iterative, Regression-Based Estimation of Haplotype Associations with Censored Survival Outcomes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-24, February.
    16. Colin O. Wu & Gang Zheng & Minjung Kwak, 2013. "A Joint Regression Analysis for Genetic Association Studies with Outcome Stratified Samples," Biometrics, The International Biometric Society, vol. 69(2), pages 417-426, June.
    17. Bhramar Mukherjee & Li Zhang & Malay Ghosh & Samiran Sinha, 2007. "Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene-Environment Independence," Biometrics, The International Biometric Society, vol. 63(3), pages 834-844, September.
    18. Tina Tsz-Ting Chui & Wen-Chung Lee, 2014. "Estimating Risks and Relative Risks in Case-Base Studies under the Assumptions of Gene-Environment Independence and Hardy-Weinberg Equilibrium," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-5, August.
    19. Megan L. Neely & Howard D. Bondell & Jung-Ying Tzeng, 2015. "A penalized likelihood approach for investigating gene–drug interactions in pharmacogenetic studies," Biometrics, The International Biometric Society, vol. 71(2), pages 529-537, June.
    20. Minin Vladimir N. & O'Brien John D. & Seregin Arseni, 2011. "Imputation Estimators Partially Correct for Model Misspecification," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-24, April.

    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:68:y:2012:i:3:p:869-877. 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.