Whittemore A S, Gong G
Department of Health Research and Policy, Stanford University School of Medicine, California 94305.
Biometrics. 1994 Dec;50(4):1073-87.
Generalized estimating equations (GEEs) (Liang and Zeger, 1986, Biometrika 73, 13-22) are used to fit genetic models to binary disease data for families of subjects in case-control studies. The GEEs include model specification of both the disease probabilities and the two-way (and possibly three-way) correlation coefficients of the family disease data. These quantities are modelled as nonlinear functions of unobserved genotypes, observed environmental covariates, and the unknown parameters; the functions reflect the method used to ascertain the family data. Goodness of fit is tested by allowing more flexible forms for the correlation coefficients, regressing them against covariates specific to the relevant pair (or triple) of family members. The approach is applied to family data obtained from simulated and real case-control studies. This semiparametric approach is less dependent on unverifiable assumptions and more computationally tractable than other methods for segregation analysis.
广义估计方程(GEEs)(Liang和Zeger,1986年,《生物统计学》73卷,第13 - 22页)用于在病例对照研究中对受试者家庭的二元疾病数据拟合遗传模型。GEEs包括疾病概率以及家庭疾病数据的双向(可能还有三向)相关系数的模型设定。这些量被建模为未观察到的基因型、观察到的环境协变量以及未知参数的非线性函数;这些函数反映了用于确定家庭数据的方法。通过允许相关系数采用更灵活的形式,并将它们针对特定家庭成员对(或三元组)的协变量进行回归,来检验拟合优度。该方法应用于从模拟和实际病例对照研究中获得的家庭数据。这种半参数方法比其他分离分析方法更少依赖不可验证的假设,并且在计算上更易于处理。