用广义估计方程估计数量性状的家庭相关

目的 研究数量性状家庭相关的测量方法，并对身高家系资料进行分析。方法 应用广义估计方程2(GEE2)估计数量性状的均数结构和关联结构的边际回归模型。所有估计都可在软件MAREG中实现。并用身高家系实例说明方法的应用。结果 GEE2可同时考虑协变量对性状的影响和性状的内部相关，得到回归系数和相关系数的稳健估计。对身高家系资料分析，调整性别、18岁前主要居住地和出生年代后，亲子相关(r=0．459)和同胞相关(r=0．671)高于配偶相关(r=0．184)，有统计学意义。同一类型亲属对中，同性别相关(如父子r=0．603，母女r=0．456，兄弟r=0．947，姐妹r=0．681)大于异性别相关(如父女r=0．431，母子r=0．364，兄妹或姐弟r=0．530)。结论 GEE2可灵活的估计各种家庭相关系数和协变量对性状均数的影响，且参数估计稳健，因此可作为评价数量性状家庭聚集性的标准方法之一。

Estimating family correlation of quantitative traits using generalized estimating equation

Objective To study the method for measuring familial correlations of quantitative trait and analyzing family data set of body height. Methods Generalized estimating equation 2(GEE2) was employed to estimating both regression coefficients and the familial correlation. Analyses was carried out on software MAREG. A example from height pedigrees illustrated the method. Results GEE2 provided robust estimations of regression coefficients and familial correlations simultaneously. In body height the correlations between parents and offspring ( r = 0.459 ) and between siblings ( r = 0.671 ) were significantly higher than those between two parents ( r = 0.184 ) after adjusting gender, residence and birth age.Of the same types of relative pairs, the correlation between pairs with individuals of the same gender (eg.father-son r = 0.603 , mother-daughter r = 0.456 , male sibling r = 0.947 , female sibling r = 0.681 ) was higher than those individuals of different gender (eg father-daughter r = 0.431 , mother- son r = 0.364 , sibling with different gender r = 0.530 ). Conclusion GEE2 should be considered a standard method for the investigation of familial aggregation due to its flexibility and robustness.