体外胚胎的处分问题研究

体外受精－胚胎移植技术产生的体外胚胎是“物”,虽然具有发展成人的潜能,但其无法取得“人”一样的权利主体地位。体外胚胎不同于一般的物,法律应予以特殊保护。中国现有法律禁止胚胎买卖,对其他处分亦应予以适当限制。从尊重胚胎与人的生育权角度看,体外胚胎应允许被继承。离异夫妻对体外胚胎处分产生分歧时,应优先考虑不愿意生养孩子一方的利益,不得将体外胚胎孕育成人。夫妻一方死亡时,另一方得在法律许可范围内处分体外胚胎。体外胚胎无人继承时,应由负责保管的医疗机构处分该胚胎。     

新传媒,新世界: 网络时代的哲学反思

新传媒正在从时空观念、经济组织形式和社会结构等方面全方位地形成一个新世界,这个新世界是一个以互联网为社会深层结构的开放世界,它的地平线已经显现。作为新世界的网络世界,有其自身的逻辑,但离不开人类的积极参与。新世界在方法论上,更倾向于归纳逻辑、认知逻辑和论辩理论。新世界的出现使人们对资本主义何时灭亡、人的主体地位等问题产生更多的开放性思考。     

福州市幼儿教师心理健康状况及其影响因素分析

采用SCL-90症状自评量表,对福州市6所幼儿园的151名幼儿教师进行测试,探讨幼儿教师心理健康状况,结果表明：心理健康水平显著低于全国成人常模;心理健康问题检出率排前三位的依次是强迫症状、抑郁、躯体化;公办园幼儿教师的心理健康状况差于民办园幼儿教师;不同学历、不同年龄、不同月收入的幼儿教师心理健康状况差别不显著;教龄高的幼儿教师心理健康状况差于教龄低的幼儿教师;对自己的收入越满意、对职业越喜欢、职业满意度越高、职业幸福感越高,则心理健康水平倾向于越高。     

A visualization method measuring the performance of biomarkers for guiding treatment decisions

Biomarkers that predict efficacy and safety for a given drug therapy become increasingly important for treatment strategy and drug evaluation in personalized medicine. Methodology for appropriately identifying and validating such biomarkers is critically needed, although it is very challenging to develop, especially in trials of terminal diseases with survival endpoints. The marker‐by‐treatment predictiveness curve serves this need by visualizing the treatment effect on survival as a function of biomarker for each treatment. In this article, we propose the weighted predictiveness curve (WPC). Based on the nature of the data, it generates predictiveness curves by utilizing either parametric or nonparametric approaches. Especially for nonparametric predictiveness curves, by incorporating local assessment techniques, it requires minimum model assumptions and provides great flexibility to visualize the marker‐by‐treatment relationship. WPC can be used to compare biomarkers and identify the one with the highest potential impact. Equally important, by simultaneously viewing several treatment‐specific predictiveness curves across the biomarker range, WPC can also guide the biomarker‐based treatment regimens. Simulations representing various scenarios are employed to evaluate the performance of WPC. Application on a well‐known liver cirrhosis trial sheds new light on the data and leads to discovery of novel patterns of treatment biomarker interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

直觉在哲学中的重要地位合理吗

直觉在哲学中的地位问题,是最近哲学界争论的一个焦点。在哲学分析与论证中,直觉具有十分重要的作用。实验哲学的大量研究发现,直觉具有多样性和差异性。直觉的可靠性因此受到了质疑,直觉的方法论地位因此受到了挑战。“直接论证直觉方法的认知地位”,“否认直觉具有显著的多样性”,“否认直觉多样性的重要性”,“否认直觉的多样性会导致不可靠性”这些策略在不同的程度上捍卫了直觉的方法论地位。正如多变的知觉在认知中具有重要地位一样,直觉的多样性与差异性并不必然动摇直觉在哲学中的地位。     

抗日文学光环掩盖下的文革

何顿的抗日题材长篇小说《来生再见》,其写作的重心不在抗日,而在文革;作家关注的不是历史,而是普通人在极端政治条件下人性的挣扎。生存环境险恶严酷的抗战时期,主人公黄抗日能够应用自己的生存哲学虎口脱身,回到家中安静地生活;但在文革的政治环境下,他却被逼得装疯、吃屎,家破人亡,生活、人格肢解得体无完肤。作品通过这种对比竖起了一座文革无字碑,形成对文革无言的控诉。     

A Note on the Large Sample Properties of Estimators Based on Generalized Linear Models for Correlated Pseudo‐observations

Pseudo‐values have proven very useful in censored data analysis in complex settings such as multi‐state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results. These results were studied more formally in Graw et al., Lifetime Data Anal., 15, 2009, 241 that derived some key results based on a second‐order von Mises expansion. However, results concerning large sample properties of estimates based on regression models for pseudo‐values still seem unclear. In this paper, we study these large sample properties in the simple setting of survival probabilities and show that the estimating function can be written as a U‐statistic of second order giving rise to an additional term that does not vanish asymptotically. We further show that previously advocated standard error estimates will typically be too large, although in many practical applications the difference will be of minor importance. We show how to estimate correctly the variability of the estimator. This is further studied in some simulation studies.     

Subgroup Analysis with Time‐to‐Event Data Under a Logistic‐Cox Mixture Model

Subgroup detection has received increasing attention recently in different fields such as clinical trials, public management and market segmentation analysis. In these fields, people often face time‐to‐event data, which are commonly subject to right censoring. This paper proposes a semiparametric Logistic‐Cox mixture model for subgroup analysis when the interested outcome is event time with right censoring. The proposed method mainly consists of a likelihood ratio‐based testing procedure for testing the existence of subgroups. The expectation–maximization iteration is applied to improve the testing power, and a model‐based bootstrap approach is developed to implement the testing procedure. When there exist subgroups, one can also use the proposed model to estimate the subgroup effect and construct predictive scores for the subgroup membership. The large sample properties of the proposed method are studied. The finite sample performance of the proposed method is assessed by simulation studies. A real data example is also provided for illustration.     

Empirical Likelihood for the Additive Hazards Model with Current Status Data

We investigate empirical likelihood for the additive hazards model with current status data. An empirical log-likelihood ratio for a vector or subvector of regression parameters is defined and its limiting distribution is shown to be a standard chi-squared distribution. The proposed inference procedure enables us to make empirical likelihood-based inference for the regression parameters. Finite sample performance of the proposed method is assessed in simulation studies to compare with that of a normal approximation method, it shows that the empirical likelihood method provides more accurate inference than the normal approximation method. A real data example is used for illustration.     

Collective versus Individual Effects in Survival Analysis of Multiple Failures

In survival analysis, we sometimes encounter data with multiple censored outcomes. Under certain scenarios, partial or even all covariates have ‘similar’ relative risks on the multiple outcomes in the Cox regression analysis. The similarity in covariate effects can be quantified using the proportionality of regression coefficients. Identifying the proportionality structure, or equivalently whether covariates have individual or collective effects, may have important scientific implications. In addition, it can lead to a smaller set of unknown parameters, which in turn results in more accurate estimation. In this article, we develop a novel approach for identifying the proportionality structure. Simulation shows the satisfactory performance of the proposed approach and its advantage over estimation under no assumed structure. We analyse three datasets to demonstrate the practical application of the proposed approach.