关于训诂批评的几个基本问题

训诂学的基本任务是维护注疏说解与文献原典本旨之间的一致性。判断文献内容与注释表达的一致性,进而进行训诂批评的客观标准是什么？这是训诂学领域里一个有待深入研究的基本理论问题。从文献原典到现代读者之间存在一个可循环链式关系,包括原典、传注、义疏、讲义、笔记等五个典型环节。各环节均由人、意、言、文等四个要素组成。“文”是训诂学者最关注的基本现象。文献是训诂的立足之本。文献里“言”与“意”的矛盾是训诂学者要面对的基本矛盾。“言”与“意”之间是不完全一致的。用反证法可以证明这条“表达不一致定律”。据此建立“表达率”和“理解率”这两个关系式,可用来解释表达上和读解中的各种现象。关于训诂的正确率问题则可以通过上述两个关系式导出答案。原典不是不可分割的整体,所以不至于完全陷入表达不一致定律的作用里。拆分原典时使用的分析单位越小,训诂正确率的值就越接近于理想值。由此可知为何传统上对汉语文献的研究往往以“字”为分析单位。最后归纳出训诂批评的四项基本标准：对原典中各个字的历史、各个词语的历史、各个词语组合情况的历史是否了解以及表达训诂结果的时候,训诂者的语言和行文是否符合规范。     

Sexual Identity in the American Deep South: The Concordance and Discordance of Sexual Activity,Relationships, and Identities

This research explores the association between sexual identity and sexual behavior and how that association varies across gender and race in the American Deep South. Multinomial logistic regression analysis is used to determine the likelihood of each sexual identity given past sexual behavior, sexual relationships, and other social characteristics. The more traditional cultural climate of the South appears to suppress identification as a sexual minority. Sexual identification in the Deep South is primarily a product of sexual activity and sexual relationships, although attitudes toward and contact with the lesbian, gay, bisexual, and transgender (LGBT) community play a minor role. Although most participants' sexual behaviors and identities were in concordance, sexual discordance was highest for White women and lowest for White men. Discordance was also associated with traditional men's roles attitudes, negative homosexuality attitudes, and contact with the LGBT community. It is hoped that these results encourage scholarship that deconstructs the sexual behavior and identity of all groups, not just oppressed groups.     

The outranking approach and the foundations of electre methods

In the first part of this paper, we describe the main features of real-world problems for which the outranking approach is appropriate and we present the concept of outranking relations. The second part is devoted to basic ideas and concepts used for building outranking relations. The definition of such outranking relations is given for the main ELECTRE methods in Part 3. The final part of the paper is devoted to some practical considerations.     

A flexible multi-stage design for phase II oncology trials

Phase II trials evaluate whether a new drug or a new therapy is worth further pursuing or certain treatments are feasible or not. A typical phase II is a single arm (open label) trial with a binary clinical endpoint (response to therapy). Although many oncology Phase II clinical trials are designed with a two-stage procedure, multi-stage design for phase II cancer clinical trials are now feasible due to increased capability of data capture. Such design adjusts for multiple analyses and variations in analysis time, and provides greater flexibility such as minimizing the number of patients treated on an ineffective therapy and identifying the minimum number of patients needed to evaluate whether the trial would warrant further development. In most of the NIH sponsored studies, the early stopping rule is determined so that the number of patients treated on an ineffective therapy is minimized. In pharmaceutical trials, it is also of importance to know as early as possible if the trial is highly promising and what is the likelihood the early conclusion can sustain. Although various methods are available to address these issues, practitioners often use disparate methods for addressing different issues and do not realize a single unified method exists. This article shows how to utilize a unified approach via a fully sequential procedure, the sequential conditional probability ratio test, to address the multiple needs of a phase II trial. We show the fully sequential program can be used to derive an optimized efficient multi-stage design for either a low activity or a high activity, to identify the minimum number of patients required to assess whether a new drug warrants further study and to adjust for unplanned interim analyses. In addition, we calculate a probability of discordance that the statistical test will conclude otherwise should the trial continue to the planned end that is usually at the sample size of a fixed sample design. This probability can be used to aid in decision making in a drug development program. All computations are based on exact binomial distribution.     

Sample size calculation for an agreement study

It is often necessary to compare two measurement methods in medicine and other experimental sciences. This problem covers a broad range of data. Many authors have explored ways of assessing the agreement of two sets of measurements. However, there has been relatively little attention to the problem of determining sample size for designing an agreement study. In this paper, a method using the interval approach for concordance is proposed to calculate sample size in conducting an agreement study. The philosophy behind this is that the concordance is satisfied when no more than the pre‐specified k discordances are found for a reasonable large sample size n since it is much easier to define a discordance pair. The goal here is to find such a reasonable large sample size n. The sample size calculation is based on two rates: the discordance rate and tolerance probability, which in turn can be used to quantify an agreement study. The proposed approach is demonstrated through a real data set. Copyright © 2009 John Wiley & Sons, Ltd.