• Title/Summary/Keyword: Kruglyak and Lander nonparametric statistic

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Comparisons of Kruglyak and Lander's Nonparametric Linkage Test and Weighted Regression Incorporating Replications (KRUGLYAK과 LANDER의 유전연관성 비모수 방법과 반복 자료를 고려한 가중 회귀분석법의 비교)

  • Choi, Eun-Kyeong;Song, Hae-Hiang
    • The Korean Journal of Applied Statistics
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    • v.21 no.1
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    • pp.1-17
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    • 2008
  • The ordinary least squares regression method of Haseman and Elston(1972) is most widely used in genetic linkage studies for continuous traits of sib pairs. Kruglyak and Lander(1995) suggested a statistic which appears to be a nonparametric counterpart to the Haseman and Elston(1972)'s regression method, but in fact these two methods are quite different. In this paper the relationships between these two methods are described and will be compared by simulation studies. One of the characteristics of the sib-pair linkage study is that the explanatory variable has only three different values and thus dependent variable is heavily replicated in each value of the explanatory variable. We propose a weighted least squares regression method which is more appropriate to this situation and the efficiency of the weighted regression in genetic linkage study was explored with normal and non-normal simulated continuous traits data. Simulation studies demonstrated that the weighted regression is more powerful than other tests.