Binary Dynamic Logit for Correlated Ordinal: estimation,application and simulation

We evaluate the estimation performance of the Binary Dynamic Logit model for correlated ordinal variables (BDLCO model), and compare it to GEE and Ordinal Logistic Regression performance in terms of bias and Mean Absolute Percentage Error (MAPE) via Monte Carlo simulation. Our results indicate that when the proportional-odds assumption does not hold, the proposed BDLCO method is superior to existing models in estimating correlated ordinal data. Moreover, this method is flexible in terms of modeling dependence and allows unequal slopes for each category, and can be used to estimate an apple bloom data set where the proportional-odds assumption is violated. We also provide a function in R to implement BDLCO.     

Repelling the “Rutter”: Social Differentiation Among Rural Teenagers

This paper examines low‐income white rural teenagers' management of race and class‐based inequality. It analyzes how these teenagers constructed boundaries to distinguish themselves from outsiders, but also to distinguish themselves from the local abject category of “rutter.” The findings reveal hidden interconnections between race and class in interactional practice, and highlight local processes of differentiation through which actors attempt to deflect stigma and attain credibility. The paper discusses how interactional mechanisms such as “internal othering” and “stigma‐theory” bolster race and class credibility, but reproduce inequality.     

Bayesian Estimation of Survival Functions under Stochastic Precedence

When estimating the distributions of two random variables, X and Y, investigators often have prior information that Y tends to be bigger than X. To formalize this prior belief, one could potentially assume stochastic ordering between X and Y, which implies Pr(X < or = z) > or = Pr(Y < or = z) for all z in the domain of X and Y. Stochastic ordering is quite restrictive, though, and this article focuses instead on Bayesian estimation of the distribution functions of X and Y under the weaker stochastic precedence constraint, Pr(X < or = Y) > or = 0.5. We consider the case where both X and Y are categorical variables with common support and develop a Gibbs sampling algorithm for posterior computation. The method is then generalized to the case where X and Y are survival times. The proposed approach is illustrated using data on survival after tumor removal for patients with malignant melanoma.     

基于随机森林模型的分类数据缺失值插补

缺失数据是影响调查问卷数据质量的重要因素,对调查问卷中的缺失值进行插补可以显著提高调查数据的质量。调查问卷的数据类型多以分类型数据为主,数据挖掘技术中的分类算法是处理属性分类问题的常用方法,随机森林模型是众多分类算法中精度较高的方法之一。将随机森林模型引入调查问卷缺失数据的插补研究中,提出了基于随机森林模型的分类数据缺失值插补方法,并根据不同的缺失模式探讨了相应的插补步骤。通过与其它方法的实证模拟比较,表明随机森林插补法得到的插补值准确度更优、可信度更高。     

康德定言命令的道德变革与实践困境

康德以纯粹理性形而上学为基础,强调善良意志和定言命令的实践理性价值.以"定言命令"为核心的道德形而上学实践理性排斥伦理学经验论,弘扬人的主体能动性,在西方伦理学引起了重大的道德哲学方向性转变.然而,"定言命令"具有形式化和僵化的普遍化特征,存在严重的形而上矛盾和现实困境,受到黑格尔等人的伦理学批判以及马克思主义唯物主义实践论的超越.     

从结果、行为到行为人：隐性采访的伦理抉择

道德困惑一直是隐性采访争论的焦点，功利主义、绝对命令、中庸之道等西方道德哲学在一定程度上能解读隐性采访面临的伦理困境。从行为的结果、行为本身到行为人，三种伦理学关注的焦点形成了一个呈逆时针方向的圆圈。功利主义是务实的，绝对命令维护了道德的纯洁性，中庸之道强调行为主体的道德修养，在这三种伦理框架的综合指导运用下，隐性采访完成了从客体到主体、由客观到主观的推理过程，伦理抉择变得更为连贯和一致，渐渐成为一种内涵。     

Multiple imputation compared with restricted pseudo‐likelihood and generalized estimating equations for analysis of binary repeated measures in clinical studies

Non‐likelihood‐based methods for repeated measures analysis of binary data in clinical trials can result in biased estimates of treatment effects and associated standard errors when the dropout process is not completely at random. We tested the utility of a multiple imputation approach in reducing these biases. Simulations were used to compare performance of multiple imputation with generalized estimating equations and restricted pseudo‐likelihood in five representative clinical trial profiles for estimating (a) overall treatment effects and (b) treatment differences at the last scheduled visit. In clinical trials with moderate to high (40–60%) dropout rates with dropouts missing at random, multiple imputation led to less biased and more precise estimates of treatment differences for binary outcomes based on underlying continuous scores. Copyright © 2005 John Wiley & Sons, Ltd.     

Survival Analysis For A Sequenced Clinical Trial With Covariates

In this paper we discuss the survival analysis for a clinical trial in which treatment categories and general prognostic data are realised at different stages during a patient's survival time. In the light of possible strategies for the parsimonious modelling of such data, a corresponding sequence of illustrative analyses is presented. Detailed results are given for a weighted least squares analysis and these generally agree with those obtained by maximum likelihood.     

汉语风格范畴的形成及其解读

“只能意会,不能言传”这一重要的命题,一直深刻地影响着中国古代哲学和诗学研究。随着西方语言学理论的传入和科学技术的发展,人们开始思考并着手试用定量的分析方法,以传统风格范畴的形成作为观察的起点,从描写和分析传统风格范畴的特征切入,寻找构成风格美感形态的基本因子为最终目标,来破解那些被认为不可言传的言语事实。     

超越性逻辑——胡塞尔现象学逻辑纲领

胡塞尔哲学的根本任务在于:坚持理性的前提下,如何建立一种非西方传统的本体论的哲学,并进而确保这种哲学的明证性。"在理性的前提下",在胡塞尔这里体现为以"逻辑研究"为核心人物;正是通过对现象学逻辑——超越逻辑的构建,胡塞尔完成了对西方传统本体论哲学的超越,具体地说,就是对西方哲学史、逻辑学史中,以公理为绝对起点,以公理体系为演绎规范的方法的超越。这种超越论的逻辑——超越论的现象学的建立,排除了以往哲学体系中的非法设定,达到了绝对的明证性;同时对于经验——自然科学的研究方式中,那种将人和自然本身的无限丰富性抽象为一种单一性的做法进行了批判,还原了以生活世界为最终根基,具有无限敞开的丰富性的真理领域。以胡塞尔逻辑学的方法来分析当今的技术、资本全球化的大背景,具有重大的启示意义。