冲突话语中冲突触发点及其回应机制——以电视剧冲突话语为例

通过分析电视剧中人物争执语言,发现这些冲突性话语都无一例外地含有一个"冲突触发点"。为深入了解其形成的动因和表现形式,采用冲突话语结构分析模式及话轮转换有关相邻对的观点,尝试对冲突性话语中冲突触发点的概念、表达形式、发生位置及其回应机制作出相关论述。结果表明:冲突触发点可以通过多种语言形式呈现,在激发和延续冲突对话方面起着关键性的作用;触发点的回应机制也存在着多样性,主要分为直接回应和间接回应两种。     

A generalized analytic solution to the win ratio to analyze a composite endpoint considering the clinical importance order among components

A composite endpoint consists of multiple endpoints combined in one outcome. It is frequently used as the primary endpoint in randomized clinical trials. There are two main disadvantages associated with the use of composite endpoints: a) in conventional analyses, all components are treated equally important; and b) in time‐to‐event analyses, the first event considered may not be the most important component. Recently Pocock et al. (2012) introduced the win ratio method to address these disadvantages. This method has two alternative approaches: the matched pair approach and the unmatched pair approach. In the unmatched pair approach, the confidence interval is constructed based on bootstrap resampling, and the hypothesis testing is based on the non‐parametric method by Finkelstein and Schoenfeld (1999). Luo et al. (2015) developed a close‐form variance estimator of the win ratio for the unmatched pair approach, based on a composite endpoint with two components and a specific algorithm determining winners, losers and ties. We extend the unmatched pair approach to provide a generalized analytical solution to both hypothesis testing and confidence interval construction for the win ratio, based on its logarithmic asymptotic distribution. This asymptotic distribution is derived via U‐statistics following Wei and Johnson (1985). We perform simulations assessing the confidence intervals constructed based on our approach versus those per the bootstrap resampling and per Luo et al. We have also applied our approach to a liver transplant Phase III study. This application and the simulation studies show that the win ratio can be a better statistical measure than the odds ratio when the importance order among components matters; and the method per our approach and that by Luo et al., although derived based on large sample theory, are not limited to a large sample, but are also good for relatively small sample sizes. Different from Pocock et al. and Luo et al., our approach is a generalized analytical method, which is valid for any algorithm determining winners, losers and ties. Copyright © 2016 John Wiley & Sons, Ltd.     

Mimicking Cox-Regression

Abstract

A class of objective functions, related to the Cox partial likelihood, that generates unbiased estimating equations is proposed. These equations allow for estimation of interest parameters when nuisance parameters are proportional to expectations. Examples of the objective functions are applied to binary data with a log-link in three situations: independent observations, independent groups of observations with common random intercept and discrete survival data. It is pointed out that the Peto–Breslow approximation to the partial likelihood with discrete failure times fits a conditional model with a log-link.     

Approximate entropy: Statistical properties and applications

ApEn, approximate entropy, is a recently developed family of parameters and statistics quantifying regularity (complexity) in data, providing an information-theoretic quantity for continuous-state processes. We provide the motivation for ApEn development, and indicate the superiority of ApEn to the K-S entropy for statistical application, and for discrimination of both correlated stochastic and noisy deterministic processes. We study the variation of ApEn with input parameter choices, reemphasizing that ApEn is a relative measure of regularity. We study the bias in the ApEn statistic, and present evidence for asymptotic normality in the ApEn distributions, assuming weak dependence. We provide a new test for the hypothesis that an underlying time-series is generated by i.i.d. variables, which does not require distribution specification. We introduce randomized ApEn, which derives an empirical significance probability that two processes differ, based on one data set from each process.     

The universal validity of the possible triangle constraint for affected sib pairs

The authors consider affected‐sib‐pair analysis, in which genetic marker data are collected from families with at least two sibs affected by a disease under investigation. At any locus not linked to the disease gene, a sib pair shares 0, 1 and 2 alleles identical by descent (IBD) with probabilities of 1/4, 1/2 and 1/4, respectively. With linkage, the IBD value increases stochastically. Louis, Payami & Thomson (1987) and Holmans (1993) were the first ones who discovered that the IBD distribution satisfies the “possible triangle constraint” in some situations. Consequently, more powerful statistical procedures can be designed in detecting linkage. It is of statistical and genetical importance to investigate whether the possible triangle constraint remains true under general genetic models. In this paper, the authors introduce a new technique to prove the possible triangle constraint. Their proof is particularly simple for the single disease locus case. The general case is proved by linking IBD distributions between marker loci through a transition probability matrix.     

联系度与初等概率

本文讨论了联系度与初等概率的关系，并比较了两者的计算结果．     

Hamilton圈计数

通过多重集排列计数，给出点标号完全三部图Kn,n,n的Hamilton圈数hn计数公式hn=（n!）^3/n∑k=0^[n/2]（2n-2k-1 n-1）（n-1 k）^2。     

Matched case–control data analyses with missing covariates

We consider methods for analysing matched case–control data when some covariates ( W ) are completely observed but other covariates ( X ) are missing for some subjects. In matched case–control studies, the complete-record analysis discards completely observed subjects if none of their matching cases or controls are completely observed. We investigate an imputation estimate obtained by solving a joint estimating equation for log-odds ratios of disease and parameters in an imputation model. Imputation estimates for coefficients of W are shown to have smaller bias and mean-square error than do estimates from the complete-record analysis.     

Likelihood methods for missing covariate data in highly stratified studies

Summary. The paper considers canonical link generalized linear models with stratum-specific nuisance intercepts and missing covariate data. This family includes the conditional logistic regression model. Existing methods for this problem, each of which uses a conditioning argu- ment to eliminate the nuisance intercept, model either the missing covariate data or the missingness process. The paper compares these methods under a common likelihood framework. The semiparametric efficient estimator is identified, and a new estimator, which reduces dependence on the model for the missing covariate, is proposed. A simulation study compares the methods with respect to efficiency and robustness to model misspecification.     

Estimation of probabilities in the class of modified power series distributions

In this paper we consider the class of modified power series distribution introduced by GUPTA (1974) and derive a minimum variance unbiased estimator (MVUE) of the probability function for this class. these results are then applied to obtain MVUE of the probability function for the generalized negative binomial distributions, the generalized poisson distribution, the generalized logarithmic series distribution and the lost game distribution. A large number of results in the literature follow trivially from out results as special cases.