Mixture Multi-state Markov Regression Model

Although heterogeneity across individuals may be reduced when a two-state process is extended into a multi-state process, the discrepancy between the observed and the predicted for some states may still exist owing to two possibilities, unobserved mixture distribution in the initial state and the effect of measured covariates on subsequent multi-state disease progression. In the present study, we developed a mixture Markov exponential regression model to take account of the above-mentioned heterogeneity across individuals (subject-to-subject variability) with a systematic model selection based on the likelihood ratio test. The model was successfully demonstrated by an empirical example on surveillance of patients with small hepatocellular carcinoma treated by non-surgical methods. The estimated results suggested that the model with the incorporation of unobserved mixture distribution behaves better than the one without. Complete and partial effects regarding risk factors on different subsequent multi-state transitions were identified using a homogeneous Markov model. The combination of both initial mixture distribution and homogeneous Markov exponential regression model makes a significant contribution to reducing heterogeneity across individuals and over time for disease progression.     

社会主义新农村建设中的新型农民

党中央提出“培养有文化、懂技术、会经营的新型农民,提高农民的整体素质”。这实际上指出了新型农民应该是有较高的思想道德素质、有一定的科学文化水平、有一定的经营管理与产业开发能力、有较强的技术辐射带动能力的农民。新型农民与传统农民的本质区别在于拥有真正的主体性,是创造主体与价值主体的统一。培养新型农民是新农村建设的题中应有之义;是建设和谐新农村的重要保证;是社会主义新农村经济发展的关键;是统筹城乡发展新思路的必然要求。     

基于模糊概率的Markowitz投资组合分散风险的理论及实证研究

在分析Markowitz模型不足的基础上，提出了一个修正模型。该模型采用模糊概率的方法对投资组合里各资产的权重进行合理调整，更准确地显现投资组合分散风险的效果，并利用实际数据对该模型进行了实证研究，验证了资产数量与组合风险之间关系的理论学说，表明在近年来的上海股票市场中适宜的投资规模不超过20种。     

信用评分模型的设计与决策分析

本文对商业银行信贷业务中的贷款者的信用问题,运用决策分析提出了信用评分的设计原理及临界分值的确定方法,给出了最优贷款策略的期望收益和风险的计算公式。最后,以一例说明之。     

A comparison of two procedures to select the best binomial population with sequential elimination of inferior populations

We compare the selection procedure of Levin and Robbins [1981. Selecting the highest probability in binomial or multinomial trials. Proc. Nat. Acad. Sci. USA 78, 4663–4666.] with the procedure of Paulson [1994. Sequential procedures for selecting the best one of k Koopman–Darmois populations. Sequential Analysis 13, 207–220.] to identify the best of several binomial populations with sequential elimination of unlikely candidates. We point out situations in which the Levin–Robbins procedure dominates the Paulson procedure in terms of the duration of the experiment, the expected total number of observations, and the expected number of failures. Because the Levin–Robbins procedure is also easier to implement than Paulson's procedure and gives a tighter guarantee for the probability of correct selection, we conclude that it holds a competitive edge over Paulson's procedure.     

A Universal QQ-Plot for Continuous Non-homogeneous Populations

This article presents a universal quantile-quantile (QQ) plot that may be used to assess the fit of a family of absolutely continuous distribution functions in a possibly non-homogeneous population. This plot is more general than probability plotting papers because it may be used for distributions having more than two parameters. It is also more general than standard quantile-quantile plots because it may be used for families of not-necessarily identical distributions. In particular, the universal QQ plot may be used in the context of non-homogeneous Poisson processes, generalized linear models, and other general models.     

国际电子合同的形式要求探析——兼评《国际合同使用电子通信公约》第9条

《国际合同使用电子通信公约》作为联合国贸法会第一部电子商务公约，对跨国电子合同的形式要求、要约邀请等进行了规范。从公约的条文入手，结合我国及他国电子商务方面的立法，分析了国际电子合同的形式要求。     

Weighted Likelihood for Semiparametric Models and Two-phase Stratified Samples, with Application to Cox Regression

Abstract.  We consider semiparametric models for which solution of Horvitz–Thompson or inverse probability weighted (IPW) likelihood equations with two-phase stratified samples leads to consistent and asymptotically Gaussian estimators of both Euclidean and non-parametric parameters. For Bernoulli (independent and identically distributed) sampling, standard theory shows that the Euclidean parameter estimator is asymptotically linear in the IPW influence function. By proving weak convergence of the IPW empirical process, and borrowing results on weighted bootstrap empirical processes, we derive a parallel asymptotic expansion for finite population stratified sampling. Several of our key results have been derived already for Cox regression with stratified case–cohort and more general survey designs. This paper is intended to help interpret this previous work and to pave the way towards a general Horvitz–Thompson approach to semiparametric inference with data from complex probability samples.     

ACCELERATED FAILURE TIME MODELS WITH NONLINEAR COVARIATES EFFECTS

As a flexible alternative to the Cox model, the accelerated failure time (AFT) model assumes that the event time of interest depends on the covariates through a regression function. The AFT model with non‐parametric covariate effects is investigated, when variable selection is desired along with estimation. Formulated in the framework of the smoothing spline analysis of variance model, the proposed method based on the Stute estimate ( Stute, 1993 [Consistent estimation under random censorship when covariables are present, J. Multivariate Anal. 45 , 89–103]) can achieve a sparse representation of the functional decomposition, by utilizing a reproducing kernel Hilbert norm penalty. Computational algorithms and theoretical properties of the proposed method are investigated. The finite sample size performance of the proposed approach is assessed via simulation studies. The primary biliary cirrhosis data is analyzed for demonstration.     

Assessing the bias due to non-coverage of residential movers in the German Microcensus Panel: an evaluation using data from the Socio-Economic Panel

The German Microcensus (MC) is a large scale rotating panel survey over three years. The MC is attractive for longitudinal analysis over the entire participation duration because of the mandatory participation and the very high case numbers (about 200000 respondents). However, as a consequence of the area sampling that is used for the MC, residential mobility is not covered and consequently statistical information at the new residence is lacking in the MC sample. This raises the question whether longitudinal analyses, like transitions between labour market states, are biased and how different methods perform that promise to reduce such a bias. Similar problems occur also for other national Labour Force Surveys (LFS) which are rotating panels and do not cover residential mobility, see Clarke and Tate (2002). Based on data of the German Socio-Economic Panel (SOEP), which covers residential mobility, we analysed the effects of missing data of residential movers by the estimation of labour force flows. By comparing the results from the complete SOEP sample and the results from the SOEP, restricted to the non-movers, we concluded that the non-coverage of the residential movers can not be ignored in Rubin’s sense. With respect to correction methods we analysed weighting by inverse mobility scores and log-linear models for partially observed contingency tables. Our results indicate that weighting by inverse mobility scores reduces the bias to about 60% whereas the official longitudinal weights obtained by calibration result in a bias reduction of about 80%. The estimation of log-linear models for non-ignorable non-response leads to very unstable results.