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分位数关联回归模型AI 解读

It is often important to study the association between two continuous variables. In this work, we propose a novel regression framework for assessing conditional associations on quantiles. We develop general methodology which permits covariate effects on both the marginal quantile models for the two variables and their quantile associations. The proposed quantile copula models have straightforward interpretation, facilitating a comprehensive view of association structure…

双变量竞争风险数据的非参数关联分析AI 解读

Although nonparametric analyses of bivariate failure times under independent censoring have been widely studied, nonparametric analyses of bivariate competing-risks data have not yet been investigated. Such analyses are important in familial association studies, where multiple interacting failure types may violate the independent censoring assumption. We develop nonparametric estimators for the bivariate cause-specific hazards function and the bivariate cumulative incidence…