Consistency measures for pairwise comparison matrices

We propose new measures of consistency of additive and multiplicative pairwise comparison matrices. These measures, the relative consistency and relative error, are easy to compute and have clear and simple algebraic and geometric meaning, interpretation and properties. The correspondence between these measures in the additive and multiplicative cases reflects the same correspondence which underpins the algebraic structure of the problem and relates naturally to the corresponding optimization models and axiom systems. The relative consistency and relative error are related to one another by the theorem of Pythagoras through the decomposition of comparison matrices into their consistent and error components. One of the conclusions of our analysis is that inconsistency is not a sufficient reason for revision of judgements. © 1998 John Wiley & Sons, Ltd.     

贵州省技区卫生服务机构准入抽查报告

深入了解我省社区卫生服务发展中存在的问题,随机抽样,现场调查。调查分析发现,社区卫生工作在我省呈现出蓬勃发展的趋势,但也暴露出了许多新的问题。应继续加强人才队伍建设,加强对社区卫生服务机构的监管,依法严格社区卫生服务机构、从业人员和技术的准入管理,制定细化的技术规范、操作规程,建立系统的考核标准、评价体系。     

大脑前扣带回皮层与执行功能

回顾了近期有关大脑前扣带回皮层（ACC）参与执行功能的研究资料。结果显示,ACC可以对正在进行的目标定向行为实施在线监控,在出现反应冲突或错误时提供信号,以便能及时调整与分配注意资源,因此可能是一个行为规划与执行的高级调控结构。这两年来的新发现提示,ACC的执行监控作用可能是基于动机与奖赏期待做出的对“意志行动”的整合性控制,并可能具有对行动结果的情绪评价意义。     

人脸图形识别取样的眼动特征

通过眼动数据的分析,探讨人脸图形识别的取样特征。实验为2×2的被试内设计,自变量为显示条件（良好显示和不良显示）和显示方式（旋转显示和非旋转显示）。实验的因变量有反应时、总注视时间、注视比率、首视点注视时间、注视点数量、扫视总距离、扫视平均距离、正确率等8个指标。被试为12名大学生,刺激材料为10幅中国人脸部图形,主要实验设备是一台Eyelinkll型服动仪。结果发现,显示条件和显示方式对人脸图形识别绩效的影响显著;随着作业难度加大,被试图形识别的首视点注视时间显著增加;人脸图形识别中,显示条件对信息取样注视比率影响显著．而显示方式显著影响信息取样点数量．     

Independence of sampling of motion parallax and binocular disparity in discrimination of depth1

Abstract: The sampling strategy of the visual system in binocular disparity and motion parallax to discriminate depth was investigated. Human observers were asked to discriminate between the depths of two surfaces defined by both cues. Gaussian noise was added to the depths represented by each cue, and the correlation in noise was manipulated. Human performance was compared with two types of likelihood models. The first was based on independent sampling, in which data from the two cues were gathered from independent sets of points in the display. The second was based on paired sampling, in which data from these cues were gathered from the same set of points. The former model yielded a better fit with human performance. This suggests that the visual system is more likely to adopt independent sampling.     

Influence of dysphoria on positive and negative cognitive reactivity to daily mood fluctuations

We used an experience sampling design to investigate the influence of dysphoria on positive and negative cognitive reactivity. Participants recorded their thoughts and mood four times per day on PDA devices for one week. We hypothesized that those higher in dysphoria would demonstrate a greater increase in negative thinking in response to negative mood, and a weaker increase in positive cognitions in response to positive mood. These hypotheses were largely supported. For those participants who reported higher initial dysphoria, there was a stronger association between negative mood and thinking and a weaker link between positive mood and thinking. Regression analyses indicated that positive and negative cognitive reactivity were independently related to dysphoria, suggesting that they represent distinct processes. Our results highlight the importance of understanding levels of both negative and positive cognitive reactivity and underscore the benefits of assessing mood and cognition with repeated measurements in "real-time," in order to better understand the antecedent effects of mood on thinking.     

汉语双字词的心理词典存储—来自发展性阅读障碍个案的证据

研究探讨了发展性阅读障碍个案S汉字命名过程选择性错误的产生机制。汉字命名、词汇判断和组词实验有三个主要发现,个案S在汉字命名过程中产生大量的选择性错误,选择性错误在复合词中发生的前后位置没有显著差异;S在词汇判断过程中,混淆词汇中两个词素的先后顺序;S对产生选择性错误的汉字组词的数量显著少于控制组,且其产生选择性错误的复合词的频率显著高于他组出的其他词汇频率。研究以Zhou&Marslen-Wilson(2000)的复合词的多水平平行结构心理词典模型为基础讨论了这些发现的理论意义,并着重分析了汉字命名过程中词素频率和词汇意义结构之间的交互作用。     

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks

The accuracy of science depends on the precision of its methods. When fields produce precise measurements, the scientific method can generate remarkable gains in knowledge. When fields produce noisy measurements, however, the scientific method is not guaranteed to work – in fact, noisy measurements are now regarded as a leading cause of the replication crisis in psychology. Scientists should therefore strive to improve the precision of their methods, especially in fields with noisy measurements. Here, we show that automation can reduce measurement error by ∼60% in one domain of developmental psychology: controlled-rearing studies of newborn chicks. Automated studies produce measurements that are 3–4 times more precise than non-automated studies and produce effect sizes that are 3–4 times larger than non-automated studies. Automation also eliminates experimenter bias and allows replications to be performed quickly and easily. We suggest that automation can be a powerful tool for improving measurement precision, producing high powered experiments, and combating the replication crisis.     

Stochastic search item selection for factor analytic models

In this paper we implement a Markov chain Monte Carlo algorithm based on the stochastic search variable selection method of George and McCulloch (1993) for identifying promising subsets of manifest variables (items) for factor analysis models. The suggested algorithm is constructed by embedding in the usual factor analysis model a normal mixture prior for the model loadings with latent indicators used to identify not only which manifest variables should be included in the model but also how each manifest variable is associated with each factor. We further extend the suggested algorithm to allow for factor selection. We also develop a detailed procedure for the specification of the prior parameters values based on the practical significance of factor loadings using ideas from the original work of George and McCulloch (1993). A straightforward Gibbs sampler is used to simulate from the joint posterior distribution of all unknown parameters and the subset of variables with the highest posterior probability is selected. The proposed method is illustrated using real and simulated data sets.