MULTIPLE-REGRESSION ANALYSIS OF TWIN DATA
MULTIPLE-REGRESSION ANALYSIS OF TWIN DATA
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DOI：
10.1007/bf01066239
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发表时间：
1985-01-01
影响因子：
2.6
通讯作者：
FULKER, DW
中科院分区：
文献类型：
--
作者：
DEFRIES, JC;FULKER, DW
本文描述了一种分析双胞胎数据的多元回归模型，其中根据先证者的S得分和关系系数(同卵双胞胎和异卵双胞胎的R分别为1.0和0.5)来预测同卵双胞胎的S得分。该模型特别适合于双胞胎的数据分析，在双胞胎中，每对中的一个成员由于异常分数而被选择，例如，阅读性能较低。当模型适用于这样的数据时，同卵双胞胎的S分数对关系系数的部分回归提供了一个强有力的检验，即先证者的平均值和未被选择的群体的平均值之间的差异是可遗传的，即遗传病因学的检验。通过将包含交互作用项的扩展模型拟合到选定或未选定的数据集，还可以获得对遗传力和由于共享环境影响引起的方差比例的直接估计(当然，服从于作为双胞胎分析基础的通常假设，例如，线性多基因模型、很少或没有分类交配，以及对于同卵双胞胎和异卵双胞胎的相同共享环境影响)。
A multiple regression model for the analysis of twin data is described in which a cotwin''s score is predicted from a proband''s score and the coefficient of relationship (R = 1.0 and 0.5 for identical and fraternal twin pairs, respectively). This model is especially appropriate for the analysis of data on twins in which one member of each pair has been selected because of a deviant score, e.g., low reading performance. When the model is fitted to such data, the partial regression of the cotwin''s score on the coefficient of relationship provides a powerful test of the extent to which the difference between the mean for probands and that for the unselected population is heritable, i.e., a test for genetic etiology. By fitting an augmented model containing an interaction term to either selected or unselected data sets, direct estimates of heritability and the proportion of variance due to shared environmental influences can also be obtained (subject, of course, to the usual assumptions underlying twin analyses, e.g., a linear polygenic model, little or no assortative mating, and equal shared environmental influences for identical and fraternal twins).