“我怀疑故我在”与“我思故我在”之区别

奥古斯丁的“我怀疑故我在”与笛卡尔的“我思故我在”这两个命题的共同之处是无需质疑的,但是它们之间的区别也是确实存在的。二者的区别主要表现在：论证的出发点、“我”的含义和论证的目的三个方面。明确这三个方面的区别将有助于我们掌握奥古斯丁教父哲学和笛卡尔哲学思想的实质。     

中国FDI区域性差异的MoranI指数分析

中国的外商直接投资呈现出东、中、西部区域非均衡分布的特征,已成为影响中国地区经济差异的重要因素。通过引入Moran I指数,文章分析了中国FDI的区域聚集效应。在此基础上,借助邓宁的区位特定优势理论,通过建立面板数据模型,分析了中国FDI区域差异性的动态原因,并将其归结为数量因子和质量因子的影响。外资流入东部地区的原因是其质量因子的区位优势,并且质量因子在后期超越了数量因子成为东部地区吸引FDI的主要因素,而中西部地区吸引FDI的主要区位优势还是其数量因子。因此,中国在外资政策导向上更应注重对"质"的把握,实现从数量型FDI到质量型FDI的转变。     

Unifying CRM and EWOC designs for phase I cancer clinical trials

The main goal of phase I cancer clinical trials is to determine the highest dose of a new therapy associated with an acceptable level of toxicity for the use in a subsequent phase II trial. The continual reassessment method (CRM) [O’Quigley, J., Pepe, M., Fisher, L., 1990. Continual reassessment method: a practical design for phase I clinical trials in cancer. Biometrics 46, 33–48] and escalation with overdose control (EWOC) [Babb, J., Rogatko, A., Zacks, S., 1998. Cancer phase I clinical trials: efficient dose escalation with overdose control. Statist. Med. 17 (10), 1103–1120] are two model-based designs used for phase I cancer clinical trials. A few modifications of the (original) CRM and EWOC have been made by many authors. In this paper, we show how CRM and EWOC can be unified and present a hybrid design. We study the characteristics of the approach of the hybrid design. The comparisons of the three designs (CRM, EWOC, and the hybrid design) are presented by convergence rates and overdose proportions. The simulation results show that the hybrid design generally has faster convergence rates than EWOC and smaller overdose proportions than CRM, especially when the true maximum tolerated dose (MTD) is above the mid-level of the dose range considered. The performance of these three designs is also evaluated in terms of sensitivity to outliers.     

Identifying the most successful dose (MSD) in dose-finding studies in cancer

For a dose finding study in cancer, the most successful dose (MSD), among a group of available doses, is that dose at which the overall success rate is the highest. This rate is the product of the rate of seeing non-toxicities together with the rate of tumor response. A successful dose finding trial in this context is one where we manage to identify the MSD in an efficient manner. In practice we may also need to consider algorithms for identifying the MSD which can incorporate certain restrictions, the most common restriction maintaining the estimated toxicity rate alone below some maximum rate. In this case the MSD may correspond to a different level than that for the unconstrained MSD and, in providing a final recommendation, it is important to underline that it is subject to the given constraint. We work with the approach described in O'Quigley et al. [Biometrics 2001; 57(4):1018-1029]. The focus of that work was dose finding in HIV where both information on toxicity and efficacy were almost immediately available. Recent cancer studies are beginning to fall under this same heading where, as before, toxicity can be quickly evaluated and, in addition, we can rely on biological markers or other measures of tumor response. Mindful of the particular context of cancer, our purpose here is to consider the methodology developed by O'Quigley et al. and its practical implementation. We also carry out a study on the doubly under-parameterized model, developed by O'Quigley et al. but not     

Adaptive phase I/II clinical trials for drug combination assessment in oncology using the outcomes of each cycle

Many new anticancer agents can be combined with existing drugs, as combining a number of drugs may be expected to have a better therapeutic effect than monotherapy owing to synergistic effects. Furthermore, to drive drug development and to reduce the associated cost, there has been a growing tendency to combine these as phase I/II trials. With respect to phase I/II oncology trials for the assessment of dose combinations, in the existing methodologies in which efficacy based on tumor response and safety based on toxicity are modeled as binary outcomes, it is not possible to enroll and treat the next cohort of patients unless the best overall response has been determined in the current cohort. Thus, the trial duration might be potentially extended to an unacceptable degree. In this study, we proposed a method that randomizes the next cohort of patients in the phase II part to the dose combination based on the estimated response rate using all the available observed data upon determination of the overall response in the current cohort. We compared the proposed method to the existing method using simulation studies. These demonstrated that the percentage of optimal dose combinations selected in the proposed method is not less than that in the existing method and that the trial duration in the proposed method is shortened compared to that in the existing method. The proposed method meets both ethical and financial requirements, and we believe it has the potential to contribute to expedite drug development.     

Notes on testing carry-over effects in continuous data under an incomplete block crossover design

We consider hypothesis testing and estimation of carry-over effects in continuous data under an incomplete block crossover design when comparing two experimental treatments with a placebo. We develop procedures for testing differential carry-over effects based on the weighted-least-squares (WLS) method. We apply Monte Carlo simulations to evaluate the performance of these test procedures in a variety of situations. We use the data regarding the forced expiratory volume in one second (FEV₁) readings taken from a double-blind crossover trial comparing two different doses of formoterol with a placebo to illustrate the use of test procedures proposed here.     

Bootstrap approach to test the homogeneity of order restricted mean vectors when the covariance matrices are unknown

Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are unknown, arbitrary positive definite and unequal are considered. This problem of testing has been studied to some extent, for example, by Kulatunga and Sasabuchi (1984 Kulatunga, D. D. S., Sasabuchi, S. (1984). A test of homogeneity of mean vectors against multivariate isotonic alternatives. Mem Fac Sci, Kyushu Univ Ser A Mathemat 38:151–161. [Google Scholar]) when the covariance matrices are known and also Sasabuchi et al. (2003 Sasabuchi, S., Tanaka, K., Tsukamodo, T. (2003). Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are common but unknown. Annals of Statistics. 31(5):1517–1536.[Web of Science ®] , [Google Scholar]) and Sasabuchi (2007 Sasabuchi, S. (2007). More powerful tests for homogeneity of multivariate normal mean vectors under an order restriction. Sankhya 69(4):700–716. [Google Scholar]) when the covariance matrices are unknown but common. In this paper, a test statistic is proposed and because of the main advantage of the bootstrap test is that it avoids the derivation of the complex null distribution analytically, a bootstrap test statistic is derived and since the proposed test statistic is location invariance the bootstrap p-value defined logical and some steps are presented to estimate it. Our numerical studies via Monte Carlo simulation show that the proposed bootstrap test can correctly control the type I error rates. The power of the test for some of the p-dimensional normal distributions is computed by Monte Carlo simulation. Also, the null distribution of test statistic is estimated using kernel density. Finally, the bootstrap test is illustrated using a real data.     

Influencing behaviour: The mindspace way

The ability to influence behaviour is central to many of the key policy challenges in areas such as health, finance and climate change. The usual route to behaviour change in economics and psychology has been to attempt to ‘change minds’ by influencing the way people think through information and incentives. There is, however, increasing evidence to suggest that ‘changing contexts’ by influencing the environments within which people act (in largely automatic ways) can have important effects on behaviour. We present a mnemonic, MINDSPACE, which gathers up the nine most robust effects that influence our behaviour in mostly automatic (rather than deliberate) ways. This framework is being used by policymakers as an accessible summary of the academic literature. To motivate further research and academic scrutiny, we provide some evidence of the effects in action and highlight some of the significant gaps in our knowledge.     

Sex, self-interest and health care priorities

In this questionnaire study, individuals were asked to prioritise publicly provided preventive health care services, one of which would be unavailable to them by virtue of their sex. The aim was to establish whether men and women would exhibit different degrees of self-interest when making a constrained choice. Around 1800 subjects from east-central England prioritised three different types of cancer screening. Most also provided written explanations for their rankings and these were classified into explanatory themes. Logistic regressions using socio-demographic and attitude data predicted the type of screening chosen as first priority. The analysis revealed that many men and women did indeed assign similar priorities to the different types of screening and, even when the priorities differed, these were often justified by similar arguments relating to technical aspects of the interventions and to self-interest. However, women were far more likely than men to prioritise a type of screening from which they themselves would benefit directly and the variations in preferences and explanations between the sexes occurred primarily because of differences in other-regarding attitudes. The bias towards screening of females was driven by women's greater worries about the disease in question and by men's “benevolent sexism” with respect to women's wellbeing.     

李约瑟与竺可桢的中国科学史研究

针对＂中国自来无科学＂的论断,以竺可桢为代表的中国学者致力于中国科学史研究,发表大量学术论著,为中国辉煌而久远的科技发展史正名;李约瑟亦不约而同地加入了大讨论,并以大量无可争辩的事实有力地批判了＂西方中心论＂。作为李约瑟《中国科学技术史》编纂强有力的支持者,竺可桢有目的地为李约瑟搜集中国科学技术史的书籍资料,并通过中国科学院给予其人力、财力资助。而李约瑟的《中国科学技术史》编撰计划实际上也诱发了竺可桢着手建立中国科学史研究专门机构的构想。就二十八宿起源地点与创立时期的学术争论,竺可桢坚持中国起源说,李约瑟则依违于巴比伦起源说与双方独立起源说之间。