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首页> 外文期刊>Journal of the Royal Statistical Society. Series C, Applied statistics >Analysis of familial aggregation in the presence of varying family sizes
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Analysis of familial aggregation in the presence of varying family sizes

机译：家庭规模不同时的家族聚集分析

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Family studies are frequently undertaken as the first step in the search for genetic and/or environmental determinants of disease. Significant familial aggregation of disease is suggestive of a genetic aetiology for the disease and may lead to more focused genetic analysis. Of course, it may also be due to shared environmental factors. Many methods have been proposed in the literature for the analysis of family studies. One model that is appealing for the simplicity of its computation and the conditional interpretation of its parameters is the quadratic exponential model. However, a limiting factor in its application is that it is not reproducible, meaning that all families must be of the same size. To increase the applicability of this model, we propose a hybrid approach in which analysis is based on the assumption of the quadratic exponential model for a selected family size and combines a missing data approach for smaller families with a marginalization approach for larger families. We apply our approach to a family study of colorectal cancer that was sponsored by the Cancer Genetics Network of the National Institutes of Health. We investigate the properties of our approach in simulation studies. Our approach applies more generally to clustered binary data.
机译：在寻找疾病的遗传和/或环境决定因素的第一步中，经常进行家庭研究。重大的家族性疾病聚集提示该疾病的遗传病因，可能导致更加集中的遗传分析。当然，这也可能是由于共享的环境因素造成的。文献中已经提出了许多用于家庭研究分析的方法。二次指数模型是简化计算和对其参数进行条件解释所吸引的一种模型。但是，其应用的限制因素是它不可复制，这意味着所有族必须具有相同的大小。为了提高该模型的适用性，我们提出了一种混合方法，其中分析基于选定家庭规模的二次指数模型的假设，并结合了针对较小家庭的缺失数据方法和针对较大家庭的边缘化方法。我们将我们的方法应用于美国国立卫生研究院癌症遗传网络赞助的大肠癌家庭研究。我们在仿真研究中研究了我们方法的性质。我们的方法更普遍地适用于群集二进制数据。

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