A technique for the nonmetric analysis of paired comparisons of psychological intervals

A nonmetric coordinate adjustment technique is developed which determines scale values for objects whose interobject intervals (differences in subjective value) have been directly compared. In Monte Carlo simulations, the degree of metric determinancy of the scale values is shown to be quite high even when the amount of error is relatively high. This robustness under high-error conditions permitted the analysis of individual subject data in experiments on the direct comparison of loudness differences and loudness ratios where only one judgment per interval comparison was obtained per subject.This research was supported by a grant from the National Research Council of Canada.     

证据顺序和证词自信度对学前末期儿童因果推理的影响

开展两个实验探究证据顺序和证词自信水平对5岁儿童因果推理的影响机制。132名和127名5岁儿童分别参与实验1和实验2。实验1发现证据顺序对儿童因果推理的影响表现为近因效应,但证词的自信水平差异不影响儿童的因果推理;实验2发现如果儿童注意到证词的自信水平信息,他们更倾向于在自信证词条件依据证词推断因果关系,证据顺序的影响力被削弱。研究结果说明证据顺序变化导致易受影响的近因效应。     

用Delta法估计多维测验合成信度的置信区间

大量研究表明,一般情况下用合成信度可以较好地估计测验信度。对于合成信度及其置信区间的估计方法,在单维测验的情形已有不少研究。但罕有研究讨论多维测验合成信度的区间估计方法。本文用Delta法推导出计算多维测验合成信度的标准误公式,进而计算置信区间,并用一个例子说明如何编程估计多维测验合成信度及其置信区间。     

Violation of the transitivity axiom may explain why, in empirical studies, a significant number of subjects violate GARP

Most papers using experimental data find that a significant number of agents are not utility function maximizers. Using three experimental datasets, we provide empirical evidence that these violations of utility function maximizing behavior are simply generated by a violation of the preference transitivity axiom. Moreover, we find that 97% of agents’ behavior is consistent with maximization of a generalized utility function called a variable intervals function (which corresponds to a numerical representation of complete-acyclic preferences).     

归纳推理多样性效应的发展及其争论

归纳推理多样性效应指的是在归纳论断中,前提项目数量越多、越多样,将能构成归纳力度越强的推理。已有研究表明成人的归纳推理明显受到前提项目多样性的影响,而幼儿的相关研究却存在着两种对立的观点：一是认为幼儿不能基于多样性进行推理,二是认为5岁左右的幼儿就能够基于多样性进行推理。出现此争论的原因可能与研究方法方面的差异有关,如实验范式与前提组间差异、实验材料类别与概念范畴、属性特征及呈现方式、推理形式;此外,儿童的知识经验也是一个影响因素。未来研究可以结合相关领域的研究范式;深入挖掘影响儿童表现出多样性效应的因素;将任务设计多样化;将实验任务的计分方式多样化;开展相关的应用研究。     

Confidence in Dyadic Decision Making: The Role of Individual Differences

Groups typically express more confidence than individuals, yet how individual‐level confidence combines during collaborative decision tasks is not well understood. We prescreened 686 community members using a novel confidence measure (a true/false trivia test) intentionally designed to be difficult (accuracy rates were not significantly better than chance) and randomly assigned 72 individuals to collaborate on a matched version of the same test in dyads composed of two low‐confidence individuals, two high‐confidence individuals, or one of each (“mixed”). Consistent with past research, we found that the confidence expressed by dyads was higher than the confidence expressed by individuals; importantly, however, this pattern varied markedly by dyad type, with low‐confidence dyads showing the largest increase, mixed dyads showing a moderate increase, and high‐confidence dyads showing no increase—despite the fact that all dyads showed similarly low accuracy (about 55%). These results highlight the conditions under which groups express greater confidence than individuals and offer insights for the composition of collaborative decision‐making teams. Copyright © 2015 John Wiley & Sons, Ltd.     

Confidently Biased: Comparisons with Anchors Bias Estimates and Increase Confidence

Across a wide variety of situations, exposure to anchors has been shown to bias people's estimates. What is not known, however, is whether externally provided anchors influence the confidence that people have in their estimates. Our studies had two goals. First, we tested whether exposure to anchors influenced people's subjective confidence levels (Studies 1 and 2). These studies revealed that people who made estimates after making comparisons with externally provided anchors tended to be more confident in their estimates than people who did not see anchors. The second goal was to test two explanations as to why anchors increase people's confidence. In Study 3, we tested the explanation that anchors increase confidence because participants thought the anchors provided useful information. In Study 4, we tested the explanation that exposure to anchors causes people to consider a narrower range of plausible values as compared to when not exposed to anchors. Support was found only for the explanation that comparisons with anchors increase confidence because people who are exposed to anchors consider a narrower range of plausible values. Taken together, these studies reveal the powerful influence anchors can have—they not only bias estimates, but also increase people's confidence in their biased estimates. Copyright © 2016 John Wiley & Sons, Ltd.     

Probabilities Associated with Precise and Vague Forecasts

Forecasts of future outcomes, such as the consequences of climate change, are given with different degrees of precision. Logically, more precise forecasts (e.g., a temperature increase of 3–4°) have a smaller probability of capturing the actual outcome than less precise forecasts (e.g., a temperature increase of 2–6°). Nevertheless, people often trust precise forecasts more than vague forecasts, perhaps because precision is associated with knowledge and expertise. In five experiments, we ask whether people expect highly confident forecasts to be associated with wider or narrower outcome ranges than less confident forecasts (Experiments 1, 2, and 5), and, conversely, whether they expect precise forecasts to be issued with higher or lower confidence than vague forecasts (Experiments 3 and 4). The results revealed two distinct ways of thinking about confidence intervals, labeled distributional (wide intervals seen as more probable than narrow intervals) and associative (wide intervals seen as more uncertain than narrow intervals). Distributional responses occurred somewhat more often in within‐subjects designs, where wide and narrow prediction intervals and high and low probability estimates can be directly compared, whereas separate evaluations (in between‐subjects design) suggested associative responses to be slightly more frequent. These findings are relevant for experts communicating forecasts through confidence intervals. Copyright © 2017 John Wiley & Sons, Ltd.     

决策信心在信息化从众中的作用

研究采用JAS范式,通过操纵群体信息的性质（支持和反对）以及一致性程度,考察了决策信心在信息化从众过程中的作用。结果表明：（1）个体仅在接收到反对信息时会发生决策的偏转,表现出从众;（2）群体参照信息能够显著影响个体的信心：支持性的群体信息使个体的信心显著增高,而反对性的群体信息使信心显著降低,且表现出一种“负性偏向”（即个体对来自群体的负性信息更加敏感）;（3）在反对条件下,个体信心降低的程度能够很好地预测其决策偏转的概率,即信息化从众行为。这说明,决策信心可能在信息化从众中起着核心的中介作用——反对性的群体信息使得决策信心下降,而决策信心的下降导致了决策的偏转,从而表现出从众行为。     

中介效应的三类区间估计方法

由于中介效应ab的估计量通常不是正态分布, 因此需用不对称置信区间进行中介效应分析。详述了三类获得不对称置信区间的方法, 包括乘积分布法(M法和经验M法)、Bootstrap方法(偏差校正和未校正的非参数百分位Bootstrap方法、偏差校正和未校正的参数百分位残差Bootstrap方法)和马尔科夫链蒙特卡罗(MCMC)方法。比较了三类方法在单层(简单和多重)和多层中介效应分析中的表现, 发现三类方法的表现相近, 与乘积分布法相比, 偏差校正的百分位Bootstrap方法表现较好, 但有先验信息的MCMC方法能更有效降低均方误。最后对中介效应不对称置信区间研究的拓展方向做了展望。