Modeling correlated survival data in genetic and biomedical research

点击翻译按钮获取中文摘要

Correlated data arise in many forms in genetic and biomedical problems, such as from studies of pairs of eyes, repeated asthma attacks, or families carrying a disease gene. In order to better understand the disease process we are studying, we need to develop new statistical models that can handle these relationships in our data. The recent progress in genetics, genomics, and other 'omics' research has created new types of correlated data that cannot be analyzed using the current methods. Two important features of these new types of data include how the patients or families were picked as well as how strong or weak the similarity is within families or pairs of eyes or asthma episodes. A statistical method that can handle this type of correlation or similarity is called a frailty model. It can be used to understand and control different types of correlation, such as a common gene, family relationships or specific environmental effects like particular foods or supplements.