农村居民看病难、看病贵原因实证分析

利用扩展的线性支出系统模型(ELES),采用最小二乘法估计计算了我国农村居民的短期医疗服务需求价格弹性。研究结果表明:农村居民的短期医疗服务需求价格缺乏弹性。由于农村居民的短期医疗服务需求价格缺乏弹性,加上我国目前医疗体制存在的以药养医和医疗机构的逐利行为以及医疗市场缺乏有效的监管等问题,导致农村居民看病难、看病贵。解决这个问题,需要国家增加对卫生领域的投入,降低农民看病时自费的比例,增强卫生市场的竞争性,适当使医疗卫生资源向农村地区倾斜,并逐渐把医疗机构办成非盈利机构。     

Backfitting Random Varying-Coefficient Models with Time-Dependent Smoothing Covariates

Abstract.  In this paper, we propose a random varying-coefficient model for longitudinal data. This model is different from the standard varying-coefficient model in the sense that the time-varying coefficients are assumed to be subject-specific, and can be considered as realizations of stochastic processes. This modelling strategy allows us to employ powerful mixed-effects modelling techniques to efficiently incorporate the within-subject and between-subject variations in the estimators of time-varying coefficients. Thus, the subject-specific feature of longitudinal data is effectively considered in the proposed model. A backfitting algorithm is proposed to estimate the coefficient functions. Simulation studies show that the proposed estimation methods are more efficient in finite-sample performance compared with the standard local least squares method. An application to an AIDS clinical study is presented to illustrate the proposed methodologies.     

在中国特色社会主义新起点上推进新的思想解放

解放思想，是党的思想路线的本质要求，是我们应对前进道路上各种新情况新问题、不断开创事业新局面的一大法宝，是中国特色社会主义的思想精髓。要把中国特色社会主义事业不断推向前进，必须在新起点上推进新的思想解放。     

对基础研究投入问题的思考

文章首先从公共财政的角度对基础研究的投入进行分析,其次从布什和斯托克斯的科研模式角度对基础研究的投入进行分析。在此基础上对加大我国基础研究的投入提出了相关建议。     

Local influence in multilevel models

The authors study the local influence of observations in multilevel regression models. To this end, they perturb simultaneously the variances, responses and design matrix. To measure the local change caused by these perturbations, they use generalized Cook statistics for the fixed and random parameter estimates. Closed form local influence measures also allow them to assess the joint influence of various observations. They suggest a simple computation method and illustrate their results using two examples.     

Modelling heterogeneous space–time occurrences of earthquakes and its residual analysis

Summary. Earthquake intensities are modelled as a function of previous activity whose specific form is based on established empirical laws in seismology, but whose parameter values can vary from place to place. This model is used for characterizing regional features of seismic activities in and around Japan, and also for exploring regions where the actual seismicity rate systematically deviates from that of the modelled rate.     

如何行成关系数据模型到面向对象数据模型的映射

关系数据模型是基于记录的基本数据模型;面向对象数据模型是基于对象的基本数据模型;两种数据模型在某种程度上应存在相互映射和相互转变的可能性,它们的相互映射和相互转变将使关系数据库和面向对象数据库之间的转变成为可能。     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.     

国外教师期望效应研究进展与当代教育启示

教师期望效应是教师对学生的期望在学生的未来发展中得到证实的现象,它反映了教师对学生的态度会影响学生发展的方向和程度,开展该现象的研究对教师观念的改变和学生的健康发展均有重要意义。对教师期望效应的种类、理论模型及国外的相关研究进行了介绍,探讨了其对教育现实的一些重要启示。