汤一介与新时期的中国哲学建设

新时期的中国哲学经历了拨乱反正、百废待举的艰难时段,也经过了各种新思潮纷至沓来、中西文化互竞优长、理论创造空前繁荣的大好时光,在中国哲学史界的一系列问题探索和热点关注中,我们都能够看到汤一介先生不知疲倦的身影。他通过魏晋玄学和早期道教的研究来探求新的方法,也试图以范畴研究的系统化来创建新的范式,对儒学的深刻反省和中国解释学的构想,更是把当代的中国哲学研究推向了一个新的高度。     

略论人的推理能力与智慧

人的智慧与其推理能力关系密切.推理能力是人的智慧的体现.学习推理是发展智慧的基础.学习推理要掌握演绎推理、归纳推理、类比推理等认识相对稳定状态的对象的推理,也要掌握认识发展变化对象的各种辩证推理.只有在实践中自觉地进行刻苦磨练,熟练地运用推理,才能产生智慧.     

抽象概念在指导性案例中的具体化方式--以最高法院指导性案例11号为例

在司法实践中,如何将法律规范中的抽象概念进行具体化阐释,是一个比较困难的问题,具有正式法律效力的指导性案例能够为解决这一问题提供提示和启发。在指导性案例11号中,司法者对“利用职务上的便利”进行了扩张解释,对“公共财产”进行了创新性的界定,其中都体现了经验、智慧和实践理性。但是,这种阐释也有一定的隐忧,包括扩张解释边界、法官能动性的发挥都不确定,法律解释方法的实用主义色彩以及忽视量刑环节等。指导性案例中对抽象概念的阐释实质上是司法实践现状与发展方向的缩影。     

Clustering objects on subsets of attributes (with discussion)

Summary.  A new procedure is proposed for clustering attribute value data. When used in conjunction with conventional distance-based clustering algorithms this procedure encourages those algorithms to detect automatically subgroups of objects that preferentially cluster on subsets of the attribute variables rather than on all of them simultaneously. The relevant attribute subsets for each individual cluster can be different and partially (or completely) overlap with those of other clusters. Enhancements for increasing sensitivity for detecting especially low cardinality groups clustering on a small subset of variables are discussed. Applications in different domains, including gene expression arrays, are presented.     

The Multivariate Randomized Complete Block Design: A Novel Permutation Solution in Case of Ordered Categorical Variables

In this article, multivariate extensions of the combination-based test statistics for the comparison of several treatments in the multivariate Randomized Complete Block designs are introduced in case of categorical response variables. Several tests for the multivariate Randomized Complete Block designs, including MANOVA procedure, are compared with the method proposed via a Monte Carlo simulation study. The method has also been applied to a real case study in the field of sensorial testing studies. Results suggest that in each experimental situation where normality of the supposed underlying continuous model is hard to justify and especially when errors have heavy-tailed distributions, the proposed nonparametric procedure can be considered as a valid solution.     

判决理由的正当性证明与法律推理

在司法实践中,判决的正当性来源于判决理由的正当性,判决理由的正当性则与法律推理密切相关。实践证明运用法律推理进行说理,将法官判决的整个过程充分呈现,可以获得判决理由的正当性证明。借助于法律推理方法实现判决理由的正当性证明是可行的,也是必要的。判决理由的正当性证明就是法律推理形式上与实质上的合法性与合理性证明,是法律推理前提和结论形成过程的推导证明。通过法律推理对判决理由进行正当性证明,可以增强判决文书的说服力,有助于判决目的的最终实现。     

Rounding non-binary categorical variables following multivariate normal imputation: evaluation of simple methods and implications for practice

We study bias arising from rounding categorical variables following multivariate normal (MVN) imputation. This task has been well studied for binary variables, but not for more general categorical variables. Three methods that assign imputed values to categories based on fixed reference points are compared using 25 specific scenarios covering variables with k=3, …, 7 categories, and five distributional shapes, and for each k=3, …, 7, we examine the distribution of bias arising over 100,000 distributions drawn from a symmetric Dirichlet distribution. We observed, on both empirical and theoretical grounds, that one method (projected-distance-based rounding) is superior to the other two methods, and that the risk of invalid inference with the best method may be too high at sample sizes n≥150 at 50% missingness, n≥250 at 30% missingness and n≥1500 at 10% missingness. Therefore, these methods are generally unsatisfactory for rounding categorical variables (with up to seven categories) following MVN imputation.     

A comparison of tests of homogeneity for sparse contingency tables

Five tests of homogeneity for a 2x(k+l) contingency table are compared using Monte Carlo techniques. For these studiesit is assumed that k becomes large in such a way that thecontingency table is sparse for 2xk of the cells, but the sample size in two of the cells remains large. The test statistics studied are: the chi-square approximation to the Pearson test statistic, the chi-square approximation to the likelihood ratio statistic, the normal approximation to Zelterman's (1984)the normal approximation to Pearson's chi-square, and the normal approximation to the likelihood ratio statistic. For the range of parameters studied the chi-square approximation to Pearson's statistic performs consistently well with regard to its size and power.     

Modeling Association Between Two or More Categorical Variables that Allow for Multiple Category Choices

Multiple-response (or pick any/c) categorical variables summarize responses to survey questions that ask “pick any” from a set of item responses. Extensions to loglinear model methodology are proposed to model associations between these variables across all their items simultaneously. Because individual item responses to a multiple-response categorical variable are likely to be correlated, the usual chi-square distributional approximations for model-comparison statistics are not appropriate. Adjusted statistics and a new bootstrap procedure are developed to facilitate distributional approximations. Odds ratio and standardized Pearson residual measures are also developed to estimate specific associations and examine deviations from a specified model.     

A score test for monotonic trend in hazard rates for grouped survival data in stratified populations

Models for monotone trends in hazard rates for grouped survival data in stratified populations are introduced, and simple closed form score statistics for testing the significance of these trends are presented. The test statistics for some of the models understudy are shown to be independent of the assumed form of the function which relates the hazard rates to the sets of monotone scores assigned to the time intervals. The procedure is applied to test monotone trends in the recovery rates of erythematous response among skin cancer patients and controls that have been irradiated with a ultraviolent challenge.