STATISTICAL MODELING FOR GENETIC EPIDEMIOLOGY

对家族性疾病和人类特征的统计检验 与疾病相关，考虑研究中的表型是否为 家族性的，如果是的话，是否有某种遗传机制(例如 主基因和与已知标记的连锁)是相关的。这样的分析 应该现实地考虑到不太具体的家庭来源 共同环境、文化传播等协变 影响单独难以区分的因素。回归模型提供了 一种实用的方法来推导必要的综合模型 家庭数据。待处理的回归模型的细节和扩展 OUT包括节俭的协变量调整；多个Logistic模型 具有两个以上类别的质量性状；基因类型的关联 配对；确定修正；丢失数据；链接和其他 双变量问题；以及方差分量和通径分析模型。这个 统计属性(偏差、一致性、诊断性、似然性 曲面，以及似然比检验的稳健性)也将被研究。

The statistical examination of familial disease, and human traits associated with diseases, considers whether the phenotype under study is familial and, if so, whether some genetic mechanism (e.g. segregation of a major gene and linkage to a known marker) is relevant. Such an analysis should realistically account for less specific sources of familial covariation such as common environment, cultural transmission and other factors with separately indistinguishable effects. Regressive models offer a practical approach to derive the necessary comprehensive models for family data. Details and extensions of the regressive models to be worked out include parsimonious covariate adjustment; multiple logistic models for qualitative traits with more than two categories; association of genotypes of mates; ascertainment corrections; missing data; linkage and other bivariate problems; and variance component and path analytic models. The statistical properties (bias, consistency, diagnostics, likelihood surfaces, and robustness of likelihood ratio tests) will also be studied.