论德里达对胡塞尔的批判

目前值得注意的是,有关德里达的众多文献都集中在他的著作上,很少有人论及他的哲学的基本内核和问津他评论其他哲学家时的哲学内含。肯定地说,德里达的信徒们总是无条件地接受随后又极力用同样的术语去重复德里达说过和解释过的东西。无论在英美分析哲学方面还是在现象学方面,严肃的哲学评论很少见,只有约翰·瑟尔例外,他是分析哲学家中唯一全面注意德里达的人。     

概念的真理与美学的真理

一、哲学与诗的冲突非理性认识与理性认识之间对立的传统和哲学本身一样地久远,甚至在柏拉图那里就曾谈及过诗与哲学之间的古老冲突,但是柏拉图始终蔑视非理性知识,常常把艺术视为诡辩。在现代,关于非理性认识的思想在德国和法国19世纪末和20世纪的哲学中相当突出,这主要是由于在存在主义以及解释学     

科技革命时代:变化的规模

整个文明时代发生了变化对每个社会中所发生的社会财富积累过程的特点进行客观分析乃是科学评价每个社会的状况和前景的标准。是谁,是哪些社会阶层以什么形式来实现这种积累,这个过程在基本居民群众的发展上是怎样反映出来的?这个过程在家庭(消费领域)的状况上,在大多数工作人员(在生产中)的状况上是怎样反映出来的?这种积累是否符合某个社会人们的主要的和决定性的需要?     

有限度的乐观:澳大利亚与中国的崛起

近年来,中国的经济增长状况以及对其未来的展望对于澳大利亚来说是非常有利的.如果像一些人预计的那样,中国在未来25年中保持强劲的增长,那么它将改变澳大利亚的经济前景,取代日本成为国家繁荣的主要推动力.中国也将改变亚洲地区:中国增长的引力作用已经使东亚经济日益整合为地区经济,而这也为更紧密的政治一体化提供了基础.     

至关重要的创造力:国家的视角

许多人从学生、教师和教育机构的角度来看待创造力的重要性,我的兴趣却在于创造力与国家繁荣之间的联系.为了在今后数十年内保持我们的生活水平,我们需要一些新的职业,而产生这些新职业离不开创造力和创新.由于创新过程本身涉及并需要新的技能,我们的大专院校必须努力在学生、教师和更广泛的社会中促进创造力的形成.     

Maximum Likelihood Estimations and EM Algorithms with Length-biased Data

Length-biased sampling has been well recognized in economics, industrial reliability, etiology applications, epidemiological, genetic and cancer screening studies. Length-biased right-censored data have a unique data structure different from traditional survival data. The nonparametric and semiparametric estimations and inference methods for traditional survival data are not directly applicable for length-biased right-censored data. We propose new expectation-maximization algorithms for estimations based on full likelihoods involving infinite dimensional parameters under three settings for length-biased data: estimating nonparametric distribution function, estimating nonparametric hazard function under an increasing failure rate constraint, and jointly estimating baseline hazards function and the covariate coefficients under the Cox proportional hazards model. Extensive empirical simulation studies show that the maximum likelihood estimators perform well with moderate sample sizes and lead to more efficient estimators compared to the estimating equation approaches. The proposed estimates are also more robust to various right-censoring mechanisms. We prove the strong consistency properties of the estimators, and establish the asymptotic normality of the semi-parametric maximum likelihood estimators under the Cox model using modern empirical processes theory. We apply the proposed methods to a prevalent cohort medical study. Supplemental materials are available online.     

一个新的稳健ARCH检验和YJ-GARCH模型

 众所周知,Engle (1982) 的ARCH检验对于条件均值模型误设并不稳健,特别地,当条件均值是非线性过程而我们仅对之建立线性模型时,它过度地拒绝真实的原假设,导致出现严重的水平扭曲 (size distortion)。因此,本文在文献当中首次利用Yeo-Johnson变换方法来转换均值模型的因变量以排除ARCH 过程中均值部分的非线性,进而提出一个新的稳健ARCH检验以及一个新的GARCH模型——Yeo-Johnson (YJ) GARCH模型。蒙特卡罗模拟结果表明,稳健的ARCH检验在水平 (size) 和势 (power) 方面的表现要显著优于Engle (1982) 的ARCH检验。对上证综指收益率的实证研究结果表明,YJ-GARCH模型的拟合效果要显著优于线性GARCH模型。     

Semi-parametric hybrid empirical likelihood inference for two-sample comparison with censored data

Two-sample comparison problems are often encountered in practical projects and have widely been studied in literature. Owing to practical demands, the research for this topic under special settings such as a semiparametric framework have also attracted great attentions. Zhou and Liang (Biometrika 92:271–282, 2005) proposed an empirical likelihood-based semi-parametric inference for the comparison of treatment effects in a two-sample problem with censored data. However, their approach is actually a pseudo-empirical likelihood and the method may not be fully efficient. In this study, we develop a new empirical likelihood-based inference under more general framework by using the hazard formulation of censored data for two sample semi-parametric hybrid models. We demonstrate that our empirical likelihood statistic converges to a standard chi-squared distribution under the null hypothesis. We further illustrate the use of the proposed test by testing the ROC curve with censored data, among others. Numerical performance of the proposed method is also examined.     

Combined survival analysis of cardiac patients by a Cox PH model and a Markov chain

The control and treatment of dyslipidemia is a major public health challenge, particularly for patients with coronary heart diseases. In this paper we propose a framework for survival analysis of patients who had a major cardiac event, focusing on assessment of the effect of changing LDL-cholesterol level and statins consumption on survival. This framework includes a Cox PH model and a Markov chain, and combines their results into reinforced conclusions regarding the factors that affect survival time. We prospectively studied 2,277 cardiac patients, and the results show high congruence between the Markov model and the PH model; both evidence that diabetes, history of stroke, peripheral vascular disease and smoking significantly increase hazard rate and reduce survival time. On the other hand, statin consumption is correlated with a lower hazard rate and longer survival time in both models. The role of such a framework in understanding the therapeutic behavior of patients and implementing effective secondary and primary prevention of heart diseases is discussed here.     

Statistical approaches for conducting network meta-analysis in drug development

We introduce health technology assessment and evidence synthesis briefly, and then concentrate on the statistical approaches used for conducting network meta-analysis (NMA) in the development and approval of new health technologies. NMA is an extension of standard meta-analysis where indirect as well as direct information is combined and can be seen as similar to the analysis of incomplete-block designs. We illustrate it with an example involving three treatments, using fixed-effects and random-effects models, and using frequentist and Bayesian approaches. As most statisticians in the pharmaceutical industry are familiar with SAS? software for analyzing clinical trials, we provide example code for each of the methods we illustrate. One issue that has been overlooked in the literature is the choice of constraints applied to random effects, and we show how this affects the estimates and standard errors and propose a symmetric set of constraints that is equivalent to most current practice. Finally, we discuss the role of statisticians in planning and carrying out NMAs and the strategy for dealing with important issues such as heterogeneity.