Simultaneous confidence band for the difference of segmented linear models

Consider comparing between two treatments a response variable, whose expectation depends on the value of a continuous covariate in some nonlinear fashion. We fit separate segmented linear models to each treatment to approximate the nonlinear relationship. For this setting, we provide a simultaneous confidence band for the difference between treatments of the expected value functions. The treatments are said to differ significantly on intervals of the covariate where the simultaneous confidence band does not contain zero. We consider segmented linear models where the locations of the changepoints are both known and unknown. The band is obtained from asymptotic results.     

Covariate Selection for the Semiparametric Additive Risk Model

Abstract.  This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared with the proportional model is, however, that there is no simple likelihood to work with. We here study a least squares criterion with desirable properties and show how this criterion can be interpreted as a prediction error. Given this criterion, we define ridge and Lasso estimators as well as an adaptive Lasso and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare the Dantzig and adaptive Lasso for a moderate to small number of covariates. The methods are applied to a breast cancer data set with gene expression recordings and to the primary biliary cirrhosis clinical data.     

Relationship Transitions Among Older Cohabitors: The Role of Health,Wealth, and Family Ties

This study explored how health, wealth, and family ties shape older cohabitors' chances of marrying or separating. Drawing on rational choice and exchange theories, the author argues these factors affect women and men differently because the rewards, alternatives, and barriers of later‐life union formation differ by gender. The study used panel data from the 1998–2006 Health and Retirement Study and a sample of cohabitors 50 and older (N = 1,136). For older female cohabitors, large families and entitlement income lower the risk of marrying, whereas close social networks raise the risk of separating. Moreover, health and wealth have an interactive relationship in that the risk of marrying is highest for unhealthy male cohabitors when they are very wealthy but is highest for the poorest female cohabitors when they are in excellent health. Older men may be exchanging economic resources for caregiving, and cohabitation may be an adaptive response to the gendered costs and barriers of later‐life union formation.     

运用整体思维审视高等教育若干抉择

高等教育不是彼此孤立的各组成部分堆成的“机械聚集体”，而是相互关联的各组成部分结成的“有机集成体”。因此，我们必须学会用整体思维方式处理各种高等教育选择问题，而此举的关键在于树立正确的高等教育局整观，即善于从整体与部分、全局与局部、系统与组分的辩证关系出发审视高等教育不同领域、不同层面的选择行为。     

高职院校竞争性选拔中层干部工作的实践与思考——以广州城市职业学院为例

文章结合广州城市职业学院中层干部竞争选拔工作的实践，阐述通过竞争性选拔干部带来的成效，同时结合高职院校的特点和实际，提出对高职院校开展全员竞争性选拔中层干部要正确处理好四个方面的关系。     

基于公文筐测验的商业银行高层管理人员选拔研究——以商业银行高级人力资源经理岗位为例

在采用文献法、访谈法和问卷法确定了银行高级人力资源管理者胜任力模型的基础上,设计和编制了适用于商业银行人力资源经理岗位的公文筐测验。研究结果表明,公文筐测验具有较高的信度和效度,可以在商业银行高层管理人员选拔中使用,但公文筐测验必须根据具体岗位来设计题目才能保证选拔的效果。     

日语专业本科毕业论文选题质量问题及对策——以文学类论文的指导为例

在本科毕业论文写作中，选题是至关重要的环节。以华南师范大学日语专业为例，通过问卷调查的方式，考察分析了影响学生毕业论文选题方向的因素。在此基础上，结合实例指出选题上存在的问题，并就如何提高文学类论文选题质量进行了探讨。     

Bayesian variable selection with spherically symmetric priors

We propose that Bayesian variable selection for linear parametrizations with Gaussian iid likelihoods should be based on the spherical symmetry of the diagonalized parameter space. Our r-prior results in closed forms for the evidence for four examples, including the hyper-g prior and the Zellner–Siow prior, which are shown to be special cases. Scenarios of a single-variable dispersion parameter and of fixed dispersion are studied, and asymptotic forms comparable to the traditional information criteria are derived. A simulation exercise shows that model comparison based on our r-prior gives good results comparable to or better than current model comparison schemes.     

On Calculations Involving the Maximum Cell Frequency

We describe a method of computing the cumulative distribution function of the maximum and minimum cell frequencies in sampling distributions commonly encountered in the analysis of categorical data.The procedure is efficient for exact or approximate calculation in both homogeneous and non-homogeneous cases, is non-recursive, and does not require Dirichlet integrals.Some related statistical problems are also discussed.     

投资组合均值-方差模型和极小极大模型的实证比较

本文针对传统的Markowitz均值-方差(MV)模型和Young(1998)提出的极小极大(Minimax)模型进行了实证比较研究。我们将2001年上证30指数的实际数据分成两部分,一部分作为样本数据进行优化组合分析,另一部分作为非样本数据进行模拟投资,检验绩效。结果发现:在同样的样本数据下,由两种模型的解描绘的风险-收益率有效前沿图非常相似;将两组模型的最优解分别进行模拟投资,Minimax模型的结果明显优于MV模型。本文的实证结果检验了Minimax模型的理论结论,表明其在实际投资中具有良好的可操作性和实用价值。