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Semiparametric analysis of case–control genetic data in the presence of environmental factors

Author

Listed:
  • Yulia V. Marchenko

    (StataCorp)

  • Raymond K. Carroll

    (Department of Statistics, Texas A&M University)

  • Danyu Y. Lin

    (Department of Biostatistics, University of North Carolina)

  • Christopher I. Amos

    (M. D. Anderson Cancer Research Center)

  • Roberto G. Gutierrez

    (StataCorp)

Abstract

In the past decade, many statistical methods have been proposed for the analysis of case-control genetic data with an emphasis on haplotype-based disease association studies. Most of the methodology has concentrated on the estimation of genetic (haplotype) main effects. Most methods accounted for environmental and gene-environment interaction effects by using prospective-type analyses that may lead to biased estimates when used with case-control data. Several recent publications addressed the issue of retrospective sampling in the analysis of case-control genetic data in the presence of environmental factors by developing efficient semiparametric statistical methods. This article describes the new Stata command haplologit, which implements efficient profile-likelihood semiparametric methods for fitting gene-environment models in the very important special cases of a rare disease, a single candidate gene in Hardy-Weinberg equilibrium, and independence of genetic and environmental factors. Copyright 2008 by StataCorp LP.

Suggested Citation

  • 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.
    • Handle: RePEc:tsj:stataj:v:8:y:2008:i:3:p:305-333
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    References listed on IDEAS

    as
    1. Mario A. Cleves, 2005. "Exploratory analysis of single nucleotide polymorphism (SNP) for quantitative traits," Stata Journal, StataCorp LP, vol. 5(2), pages 141-153, June.
    2. 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.
    3. 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.
    4. A. P. Mander, 2001. "Haplotype analysis in population-based association studies," Stata Journal, StataCorp LP, vol. 1(1), pages 58-75, November.
    5. Liu, Yuanli & Rao, Keqin & Hu, Teh-wei & Sun, Qi & Mao, Zhenzhong, 2006. "Cigarette smoking and poverty in China," Social Science & Medicine, Elsevier, vol. 63(11), pages 2784-2790, December.
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    Cited by:

    1. Elisa Rossi & Daniela Basso & Carlo-Federico Zambon & Filippo Navaglia & Eliana Greco & Michela Pelloso & Serena Artuso & Andrea Padoan & Matilde Pescarin & Ada Aita & Dania Bozzato & Stefania Moz & M, 2015. "TNFA Haplotype Genetic Testing Improves HLA in Estimating the Risk of Celiac Disease in Children," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.

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