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双重删失数据下的回归 M 估计AI 解读

The M-estimators are proposed for the linear regression model with random design when the response observations are doubly censored. The proposed estimators are constructed as some functional of a Campbell-type estimator $\hat{F}_n$ for a bivariate distribution function based on data which are doubly censored in one coordinate. We establish strong uniform consistency and asymptotic normality of $\hat{F}_n$ and derive the asymptotic normality of the proposed regression…

分批入组 Cox 模型的一般渐近理论AI 解读

A general asymptotic theory is established for the two-parameter Cox score process with staggered entry data. It extends in several directions the existing theory developed by Sellke and Siegmund, Slud and Gu and Lai. An essential tool employed here is a modern empirical process theory, as elucidated in a recent monograph by Pollard.

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一般相对风险回归中参数可识别性与偏似然有效性札记AI 解读

In this note we deal with the question of identifiability of the regression parameter in general relative risk regression. We show that, apart from the well understood kind of nonidentifiability, as usually occurs with regression, there is a second kind of nonidentiliability of the regression parameter which may still be present even if the information matrix is positive definite. However, when this happens, the partial likelihood approach is still valid, even though some…

删失回归数据的序贯分析AI 解读

Motivated by Buckley and James' modification of the least squares procedure for censored regression data, we derive a score process that incorporates the time evolution and handles staggered entry data in a natural way. By censored regression data we mean that the responses are subject to a possible right censorship. Such cases often arise from clinical trials and industrial life tests. The score process can be interpreted as a weighted comparison of (transformed) survival…

删失回归数据的序贯分析AI 解读

Motivated by Buckley and James' modification of the least squares procedure for censored regression data, we derive a score process that incorporates the time evolution and handles staggered entry data in a natural way. By censored regression data we mean that the responses are subject to a possible right censorship. Such cases often arise from clinical trials and industrial life tests. The score process can be interpreted as a weighted comparison of (transformed) survival…