SINGLE‐SAMPLE DISCRIMINATION OF DIFFERENT SCHEDULES' REINFORCED INTERRESPONSE TIMES

Food‐deprived rats in Experiment 1 responded to one of two tandem schedules that were, with equal probability, associated with a sample lever. The tandem schedules' initial links were different random‐interval schedules. Their values were adjusted to approximate equality in time to completing each tandem schedule's response requirements. The tandem schedules differed in their terminal links: One reinforced short interresponse times; the other reinforced long ones. Tandem‐schedule completion presented two comparison levers, one of which was associated with each tandem schedule. Pressing the lever associated with the sample‐lever tandem schedule produced a food pellet. Pressing the other produced a blackout. The difference between terminal‐link reinforced interresponse times varied across 10‐trial blocks within a session. Conditional‐discrimination accuracy increased with the size of the temporal difference between terminal‐link reinforced interresponse times. In Experiment 2, one tandem schedule was replaced by a random ratio, while the comparison schedule was either a tandem schedule that only reinforced long interresponse times or a random‐interval schedule. Again, conditional‐discrimination accuracy increased with the temporal difference between the two schedules' reinforced interresponse times. Most rats mastered the discrimination between random ratio and random interval, showing that the interresponse times reinforced by these schedules can serve to discriminate between these schedules.     

Testing the latent factor structure and construct validity of the Ten-Item Personality Inventory

Recent efforts have aimed to develop relatively short measures of the Five-Factor Model (FFM) of personality, particularly for when time and/or space is limited. We evaluate the Ten-Item Personality Inventory (TIPI), a non-proprietary FFM measure with two items per dimension. We use a latent variable methodology to examine the TIPI’s factor structure and convergent validity with the 50-item International Personality Item Pool (IPIP) FFM measure. We provide correlations between the scale scores and latent factors, and compare each measure’s pattern of correlations with measures of other individual difference constructs. Results were favorable in terms of the factor structure and convergent validity of the TIPI, particularly regarding the correlations between the respective latent factors of the TIPI and the IPIP–FFM measures.     

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。     

学习因素对语义信息加工性质的影响

本研究通过两个行为实验,采用句子核证作业,将SAD技术和范畴学习范式有机地结合起来,对语义信息加工进程以及学习因素在其中的作用进行了考察。实验一研究了熟悉性对语义信息加工的影响。结果表明,高熟悉句的部分信息积累具有离散的趋势;低熟悉句的部分信息积累是连续性的。实验二采用范畴学习。并结合SAD技术的句子核证作业．考察了在学习过程中语义加工性质的变化。结果发现：过度学习比初始学习有更多的部分信息积累,并随信号间隔的延长而逐渐增加;过度学习表现出部分信息积累的离散性变化;初始学习则表现出连续累积的趋势。说明学习确实造成了连续性加工向离散性质的过渡。     

Determinants of reinforcer accumulation during an operant task.

Responses by rats on an earn lever made available food pellets that were delivered to a food cup by responses on a second, collect, lever. The rats could either collect and immediately consume or accumulate (defined as the percentage of multiple earn responses and as the number of pellets earned before a collect response) earned pellets. In Experiment 1, accumulation varied as a function of variations in the earn or collect response requirements and whether the earn and collect levers were proximal (31 cm) or distal (248 cm) to one another. Some accumulation occurred under all but one of the conditions, but generally was higher when the earn and collect levers were distal to one another, particularly when the earn response requirement was fixed-ratio (FR) 1. In Experiment 2, the contributions of responses and time to accumulation were assessed by comparing an FR 20 earn response requirement to a condition in which only a single earn response was required at the end of a time interval nominally yoked to the FR interval. When 248 cm separated the earn and collect levers, accumulation was always greater in the FR condition, and it was not systematically related to reinforcement rate. In Experiment 3, increasing the earn response requirement with a progressive-ratio schedule that reset only with a collect response increased the likelihood of accumulation when the collect and earn levers were 248 cm apart, even though such accumulation increased the next earn response requirement. Reinforcer accumulation is an understudied dimension of operant behavior that relates to the analysis of such phenomena as hoarding and self-control, in that they too involve accumulating versus immediately collecting or consuming reinforcers.     

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.