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利用家庭数据估计遗传关联参数AI 解读

We consider the problem of estimating a parameter θ reflecting association between a disease and genotypes of a genetic polymorphism, using nuclear family data. In many applications, some parental genotypes are missing, and the distribution of these genotypes is unknown. Since misspecification of this distribution can bias estimators for θ, we consider estimating functions that are unbiased, regardless of how the distribution is specified. We call the resulting estimators…

病例对照研究中家庭数据的 Logistic 回归AI 解读

Multivariate regression models are applied to binary disease data in families identified from case-control studies. Attention is restricted to ‘ marginal’ or reproducible models, i. e. those whose parameters have the same interpretations in the marginal distributions for all subsets of a family, with a logistic specification of each individual's marginal disease probability. For such models, it is shown that the case-control family data can be analysed as if they were…