EXTENSIONS TO MULTIVARIATE NORMAL-MODELS FOR PEDIGREE ANALYSIS
EXTENSIONS TO MULTIVARIATE NORMAL-MODELS FOR PEDIGREE ANALYSIS
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DOI：
10.1111/j.1469-1809.1982.tb01588.x
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发表时间：
1982-01-01
影响因子：
1.9
通讯作者：
MATHEWS, JD
中科院分区：
文献类型：
--
作者：
HOPPER, JL;MATHEWS, JD
Lange，韦斯特莱克& Spence（1976）使用多变量正态性的假设，将似然方法应用于系谱上测量的数量性状的分析。我们现在介绍多元正态性假设的检验和检测边远家庭和边远个人的方法。我们还介绍了一种方法，用于估计测量的遗传标记作为方差分量的影响，一个灵活的参数化，以估计共享的家庭环境的影响，并允许通过先证者确定家系的方法。这些创新已被应用于使用数值方法的可能性最大化。模拟研究和现有的理论表明，显着性检验中使用的似然比准则遵循典型应用中遇到的样本大小的预期渐近分布。
Lange, Westlake & Spence (1976) used the assumption of multivariate normality to apply a likelihood method to the analysis of quantitative traits measured over pedigrees. We now introduce a test of the assumption of multivariate normality and methods for the detection of outlying families and outlying individuals. We also introduce a method for the estimation of effects of measured genetic markers as variance components, a flexible parameterization to estimate effects of shared family environment, and a method to allow for the ascertainment of pedigrees through probands. These innovations have been applied using numerical methods for maximization of the likelihood. Simulation studies and available theory suggest that the likelihood ratio criterion used in significance testing follows the expected asymptotic distribution with sample sizes encountered in typical applications.