Lange K, Westlake J, Spence M A
Ann Hum Genet. 1976 May;39(4):485-91. doi: 10.1111/j.1469-1809.1976.tb00156.x.
The classic variance components for simple polygenic traits - additive, dominance, and environmental variance - have traditionally been estimated from sample covariances between first-degree relatives. If data is gathered on pedigrees, this statistical procedure wastes information. Recently Elston & Stewart suggested an alternative likelihood procedure that uses all the information in a set of pedigrees. A refinement of their method based on the scoring technique gives rapidly converging maximum likelihood estimates of the variance components and of the male and female means. Tests of statistical hypotheses about the various parameters can then be made by the likelihood ratio method. Furthermore, using classical regression analysis, the estimated parameter values allow prediction of unknown trait values from known trait values within a pedigree. These methods should apply to traits like total finger ridge count and to quantitative measurements associated with disease traits. Since the model postulates independent environmental effects and no assortative mating, its utility in human behaviour genetics seems limited.
对于简单多基因性状的经典方差成分——加性、显性和环境方差——传统上是通过一级亲属之间的样本协方差来估计的。如果收集的是家系数据,这种统计方法会浪费信息。最近,埃尔斯顿和斯图尔特提出了一种替代的似然方法,该方法利用一组家系中的所有信息。基于评分技术对他们方法的改进给出了方差成分以及男性和女性均值的快速收敛的最大似然估计。然后可以通过似然比方法对各种参数进行统计假设检验。此外,使用经典回归分析,估计的参数值允许根据家系内已知的性状值预测未知的性状值。这些方法应该适用于诸如总指嵴数等性状以及与疾病性状相关的定量测量。由于该模型假设环境效应独立且不存在选型交配,其在人类行为遗传学中的效用似乎有限。