A new reproducing kernel-based nonlinear dimension reduction method for survival data

Based on the theories of sliced inverse regression (SIR) and reproducing kernel Hilbert space (RKHS), a new approach RDSIR (RKHS-based Double SIR) to nonlinear dimension reduction for survival data is proposed. An isometric isomorphism is constructed based on the RKHS property, then the nonlinear function in the RKHS can be represented by the inner product of two elements that reside in the isomorphic feature space. Due to the censorship of survival data, double slicing is used to estimate the weight function to adjust for the censoring bias. The nonlinear sufficient dimension reduction (SDR) subspace is estimated by a generalized eigen-decomposition problem. The asymptotic property of the estimator is established based on the perturbation theory. Finally, the performance of RDSIR is illustrated on simulated and real data. The numerical results show that RDSIR is comparable with the linear SDR method. Most importantly, RDSIR can also effectively extract nonlinearity from survival data.     

Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates,with application to analysis of biomarker correlates in vaccine trials

This article presents generalized semiparametric regression models for conditional cumulative incidence functions with competing risks data when covariates are missing by sampling design or happenstance. A doubly robust augmented inverse probability weighted (AIPW) complete-case approach to estimation and inference is investigated. This approach modifies IPW complete-case estimating equations by exploiting the key features in the relationship between the missing covariates and the phase-one data to improve efficiency. An iterative numerical procedure is derived to solve the nonlinear estimating equations. The asymptotic properties of the proposed estimators are established. A simulation study examining the finite-sample performances of the proposed estimators shows that the AIPW estimators are more efficient than the IPW estimators. The developed method is applied to the RV144 HIV-1 vaccine efficacy trial to investigate vaccine-induced IgG binding antibodies to HIV-1 as correlates of acquisition of HIV-1 infection while taking account of whether the HIV-1 sequences are near or far from the HIV-1 sequences represented in the vaccine construct.     

浅谈如何发挥综合统计在高校管理中的作用

通过分析统计工作现状，认为正确认识并充分发挥综合统计工作的积极作用是解决目前高校管理中存在问题的重要途径。文章分别从为领导决策服务功能、查询服务功能、监督功能以及对其他管理工作的促进作用四方面阐述综合统计工作的重要作用。     

农地抵押贷款试点政策对农民收入的增长效应研究

文章基于2013—2019年湖南省县域面板数据,采用双重差分方法识别了农地抵押贷款试点对农民收入增长的效应。研究发现:政策对农民收入增长效应显著为正,效果提高约3.84%,以多种稳健性检验,此结论依然成立。这一政策对邻近区县具有正向溢出效应,政策效果非贫困区县强于贫困区县。此外,农地抵押贷款试点主要通过农业扶持、产业扶持、金融扶持、城市化提升等措施对当地农民收入产生间接影响,更重要的是,政策通过相应精准扶持措施促进政策效应,但仍然需要降低融资壁垒,促进农村金融农地抵押融资。研究结果进一步强调了农地抵押贷款试点需根据地区实际发展情况,因时因地因户精准施策的重要性。     

Preference for Flexibility in a Savage Framework

We study preferences over Savage acts that map states to opportunity sets and satisfy the Savage axioms. Preferences over opportunity sets may exhibit a preference for flexibility due to an implicit uncertainty about future preferences reflecting anticipated unforeseen contingencies. The main result of this paper characterizes maximization of the expected indirect utility in terms of an ‘Indirect Stochastic Dominance’ axiom that expresses a preference for ‘more opportunities in expectation.’ The key technical tool of the paper, a version of Möbius inversion, has been imported from the theory of nonadditive belief functions; it allows an alternative representation using Choquet integration, and yields a simple proof of Kreps' (1979) classic result.     

基于Logistic模型的财富逆转移因素分析及程度测定

构建Logistic回归模型,并以北京市为例测定其财富逆转移程度.从财富逆转移的角度研究城市贫富差距扩大会导致公共危机的爆发,要素价格扭曲、转移支付体系不健全、市场机会不均、房价等因素直接影响社会财富的逆转移,并进一步扩大城市的贫富差距.结果表明:2013年的财富逆转移程度略大于2008年.政府可以通过降低要素价格的扭曲程度,不断完善税收和转移支付体系,加强就业及促进市场机会均等,控制房价的上涨速度,来减缓财富的逆转移程度.