影响整合式谈判的情境因素和过程因素

从“情境因素”和“过程因素”两个方面对整合式谈判影响因素的研究动态和研究成果进行了归纳和分析。其中“情境因素”是指在正式谈判一开始时就已经存在的因素,主要包括：（1）谈判者的文化价值观,如个人主义与集体主义、权力距离和沟通的高、低语境;（2）社会动机,研究谈判组的动机构成如何影响谈判过程和结果;（3）情绪因素,研究谈判中的积极情绪、消极情绪各自对达成整合式谈判的影响。对“过程因素”的研究考察了谈判沟通的过程,包括谈判过程中各种策略的使用频次、次序和谈判各个阶段的策略使用情况     

A Bayesian Semiparametric Latent Variable Model for Mixed Responses

In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semiparametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear effects of continuous covariates and interactions with other covariates as well as spatial effects. Full Bayesian modelling is based on penalized spline and Markov random field priors and is performed by computationally efficient Markov chain Monte Carlo (MCMC) methods. We apply our approach to a German social science survey which motivated our methodological development. We thank the editor and the referees for their constructive and helpful comments, leading to substantial improvements of a first version, and Sven Steinert for computational assistance. Partial financial support from the SFB 386 “Statistical Analysis of Discrete Structures” is also acknowledged.     

澳门人的风险知觉与赌博行为

采用匿名问卷法,调查澳门人的风险知觉与赌博行为。结果显示：（1）赌场的劝世文既无劝勉也无劝阻人们赌博的作用;（2）社会关系网的钱财支援不影响实际赌博次数;（3）多次性博弈与一次性博弈所采用的是不同的机制,一次性博弈不是由期望值所决定的;（4）相互监视和制裁系统会影响赌博：受法律制裁约束的职业者比不受法律制裁约束的职业者更不好赌;自估在赌场遇见认识人的机会与赌博次数呈负相关;（5）性别及母语等“本质趋向”差异表明,所谓澳门人不好赌有其渊源并可能是在长期的文化沉淀中形成的;（6）受教育程度是影响赌博的有效预测变量。这些发现的理论含义一并进行了讨论。     

A variable-selection heuristic for K-means clustering

One of the most vexing problems in cluster analysis is the selection and/or weighting of variables in order to include those that truly define cluster structure, while eliminating those that might mask such structure. This paper presents a variable-selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. The heuristic was subjected to Monte Carlo testing across more than 2200 datasets with known cluster structure. The results indicate the heuristic is extremely effective at eliminating masking variables. A cluster analysis of real-world financial services data revealed that using the variable-selection heuristic prior to the K-means algorithm resulted in greater cluster stability.     

An overview of applied robust methods

Data in social sciences are typically non-normally distributed and characterized by heavy tails. However, most widely used methods in social sciences are still based on the analyses of sample means and sample covariances. While these conventional methods continue to be used to address new substantive issues, conclusions reached can be inaccurate or misleading. Although there is no ‘best method’ in practice, robust methods that consider the distribution of the data can perform substantially better than the conventional methods. This article gives an overview of robust procedures, emphasizing a few that have been repeatedly shown to work well for models that are widely used in social and behavioural sciences. Real data examples show how to use the robust methods for latent variable models and for moderated mediation analysis when a regression model contains categorical covariates and product terms. Results and logical analyses indicate that robust methods yield more efficient parameter estimates, more reliable model evaluation, more reliable model/data diagnostics, and more trustworthy conclusions when conducting replication studies. R and SAS programs are provided for routine applications of the recommended robust method.     

A bayesian estimation of factor score in confirmatory factor model with polytomous, censored or truncated data

The posterior analysis in estimating factor score in a confirmatory factor analysis model with polytomous, censored or truncated data is investigated in this paper. For the above three types of data, posterior distributions of the factor score are studied, and the estimators of the factor score are obtained to be the location parameters of the posterior distributions. The accuracy of Bayesian estimates is studied via simulation studies.This research was supported by a Hong Kong UGC grant.     

The effects of nodality on the formation of equivalence classes

A four-member equivalence class (A → B → C → D) can be formed by training AB, BC, and CD. The nodal stimuli, B and C, mediate all of the derivative (transitive and equivalence) relations in the class. The derivative relations AC, CA, BD, and DB are separated by one node, whereas AD and DA are separated by two nodes. How do the number of nodes that separate the stimuli in a derivative relation influence the induction of stimulus control exerted by that relation? Seven college students learned two four-member classes made up of nonsense syllables. After training, all derivative relations were presented repeatedly without informative feedback. Stimulus control exerted by each derivative relation was assessed concurrently. For the 7 subjects, control exerted by the derivative relations increased gradually with repeated presentations. With 6 of the 7 subjects, the one-node relations exerted more control than the two-node relations during the process. However, the disparity between the one- and two-node relations decreased with repeated presentations. Eventually, all derivative relations exerted complete control. The control exerted by derivative relations during induction was inversely related to the number of nodes separating the terms in the derivative relations. These results demonstrate that nodal distance is a determinant of the relatedness of stimuli in equivalence classes. The findings are discussed in terms of remote association, semantic memory networks, and the study of transitive inference.     

Stimulus-specific contrast effects during operant discrimination learning

In two experiments, pigeons' responding was equally reinforced in the presence of four line-orientation stimuli. Responding was then reinforced when only two of the four orientation stimuli were present; the remaining two orientations appeared during extinction. Response rates were often highest in the stimulus adjacent to the orientations presented during extinction and often lowest in that orientation adjacent to the orientations presented with reinforcement. These effects were stronger and more persistent when the stimuli were separated by a smaller angle, rendering the discrimination more difficult. These and other data suggest that discrimination training may not be accurately explained in terms of the simple effects of reinforcement and nonreinforcement associated with isolated stimuli, nor by accounts that depend upon stimulus generalization. Recent accounts of contrast that depend upon “emotionality” produced by nonreinforced responding or upon reinforcement-elicited responses are also difficult to apply to these data.     

Matching with a trio of concurrent variable-interval schedules of reinforcement

A trio of concurrent variable-interval schedules of reinforcement was arranged according to a changeover-key procedure, including a changeover delay of 1.5 sec. The three schedules provided a combined maximum reinforcement rate of 45 reinforcements per hour. With that restriction, the nine experimental conditions included several combinations of variable-interval schedules, sometimes including extinction. The pigeons matched relative response rate and relative time to relative reinforcement rate. Relative time appeared to match some-what better than relative response rate. Performance adjusted rapidly from one experimental condition to the next, whether the change involved two or all three schedules of the concurrent trio.