Lee H, Stram D O, Thomas D C
Department of Preventive Medicine, University of Southern California, Los Angeles.
Genet Epidemiol. 1993;10(1):61-74. doi: 10.1002/gepi.1370100107.
This paper discusses the application of estimating equations methods based on a quadratic exponential model [Prentice and Zhao, 1991] as a potential competitor with full likelihood approaches to estimating the effect of major genes in a segregation analysis [Elston, 1981] of continuous phenotypes, in the single allele problem. We show that while the estimating equations methods based on the quadratic exponential family cannot be used by themselves to estimate all parameters of interest, an iterative two-stage approach can be used, in which the population allele frequency is first considered to be a known parameter, which permits the estimating equations method to estimate the remaining parameters. At the second stage a "pseudo-profile" loglikelihood based only on the founders is used to estimate the allele frequency. After each maximization of the pseudo-profile loglikelihood at the second stage, the parameters in the first stage are reestimated using a new value of the allele frequency, and a new value of the second stage pseudo-profile loglikelihood is obtained. We used simulated pedigree data for illustrations.
本文讨论了基于二次指数模型的估计方程方法的应用[普伦蒂斯和赵，1991]，作为在单等位基因问题中对连续性状进行分离分析[埃尔斯顿，1981]时估计主基因效应的全似然方法的潜在竞争对手。我们表明，虽然基于二次指数族的估计方程方法本身不能用于估计所有感兴趣的参数，但可以使用迭代两阶段方法，其中首先将群体等位基因频率视为已知参数，这允许估计方程方法估计其余参数。在第二阶段，仅基于创始人的“伪轮廓”对数似然用于估计等位基因频率。在第二阶段每次最大化伪轮廓对数似然后，使用等位基因频率的新值重新估计第一阶段的参数，并获得第二阶段伪轮廓对数似然的新值。我们使用模拟系谱数据进行说明。
