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Group sequential testing of homogeneity in genetic linkage analysis

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  • Cui, Yin
  • Fu, Yuejiao
  • Hussein, Abdulkadir

Abstract

Human genetic linkage studies have the objective of testing whether disease genes are linked to genetic markers based on family genetic data. Sometimes, these studies require many years of recruiting informative families and large amount of funds. One way to reduce the required sample size for such studies is to use sequential testing procedures. In this paper, we investigate two group sequential tests for homogeneity in binomial mixture models that are commonly used in genetic linkage analysis. We conduct Monte Carlo simulations to examine the performance of the group sequential procedures. The results show that the proposed group sequential procedures can save, on average, substantial sample size and detect linkage with almost the same power as their nonsequential counterparts.

Suggested Citation

  • Cui, Yin & Fu, Yuejiao & Hussein, Abdulkadir, 2009. "Group sequential testing of homogeneity in genetic linkage analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3630-3639, August.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:10:p:3630-3639
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    References listed on IDEAS

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    1. Kung-Yee Liang & Paul J. Rathouz, 1999. "Hypothesis Testing Under Mixture Models: Application to Genetic Linkage Analysis," Biometrics, The International Biometric Society, vol. 55(1), pages 65-74, March.
    2. Hanfeng Chen & Jiahua Chen & John D. Kalbfleisch, 2004. "Testing for a finite mixture model with two components," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 95-115, February.
    3. Hanfeng Chen & Jiahua Chen & John D. Kalbfleisch, 2001. "A modified likelihood ratio test for homogeneity in finite mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 19-29.
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    Cited by:

    1. Sengupta, Raghu Nandan & Sengupta, Angana, 2011. "Some variants of adaptive sampling procedures and their applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3183-3196, December.
    2. A. Hussein & H. Muttlak & E. Al-Sawi, 2013. "Group sequential methods based on ranked set samples," Statistical Papers, Springer, vol. 54(3), pages 547-562, August.
    3. Todd, Susan & Fazil Baksh, M. & Whitehead, John, 2012. "Sequential methods for pharmacogenetic studies," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1221-1231.

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