Braine心理逻辑理论述评

该文对Braine提出的在推理心理学研究领域占居重要地位的“心理逻辑理论”做了综合述评。“心理逻辑理论”主要包括三方面内容:构成“心理逻辑理论”基础的一组推理规则图式、将推理规则图式应用于推理过程的推理方案、实际应用意义。Braine认为他和他的同事于1984年设计并实施的以“自然推理系统”所含各推理规则为实验材料的实验结果支持该理论的基本观点。     

Relationships Between Treatment Components, Client-Level Factors, and Positive Treatment Outcomes

How different amounts and components of treatment affect substance abuse treatment outcomes is fundamentally important to evaluating current treatment practices and recommending improvements. Through a secondary analysis of data from the National Treatment Improvement Evaluation Study (NTIES), the present study examined the relationships between treatment components, client-level factors, and positive treatment outcomes. Several components were shown tohave significant effects on the odds of a positive outcome, over and above the effects of client background characteristics. Depending on treatment modality, these included length of stay; whether or not clients reported seeing their treatment plan hours per month in group and individual counseling; utilization ofeducational, vocational, and other ancillary services; use of antianxiety and drug and alcohol medications; and client matching. Several interactions between client-level factors and treatment components were also observed. Studylimitations are discussed, followed by implications for policy and practiceand suggestions for further research.     

回溯式时间记忆特点的实验研究

实验研究在2个月的时间内探索了回溯式时间记忆的特点,实验选取15个影视片断和8个新闻事件,影视片段播放的时间和新闻事件的发生同期,要求被试回忆影视片段和新闻事件的时点、时距和时序。结果表明：（1）在时序上,影视片段时序的准确性高于新闻事件;在时距上,7分钟和15分钟的准确性高于30分钟,7分钟时距倾向于高估,30分钟时距倾向于低估;在时点上,影视片段的准确性高于新闻事件。（2）时点的回溯式记忆受到被试自我卷入程度的影响。（3）回溯式时距估计受到真实时距的长短和延迟时间长短的交互影响。（4）事件序列关系一般倾向于具有网络层次的特征,在无充足思考时间条件下,倾向于具有线形模型的特征。     

高中生的亲子沟通质量对情绪性刺激注意偏向的影响

为了探讨高中生亲子沟通质量对情绪性刺激注意偏向的影响,实验一采用亲子沟通量表,筛选出亲子沟通高分组和低分组,两组被试参加点探测任务,要求被试迅速判断情绪性图片出现后呈现的圆点的位置。实验为2（组别：高亲子沟通组、低亲子沟通组）×2（情绪类型：负性和正性）×2（探测点位置一致性：一致、不一致）的混合实验设计。结果发现,负性和正性刺激的不一致条件反应时均显著短于一致条件的反应时。实验二采用事件相关电位（ERP）记录了情绪性图片诱发的信号反应。结果发现,亲子沟通高分组对负性刺激所诱发的注意指向和集中（P2成分）及选择和巩固（P3成分）显著高于低分组。以上结果表明,亲子沟通较好,在注意早期定向和选择中会对负性情绪刺激产生注意偏向。亲子沟通较差,则对情绪性的刺激没有明显的偏向性,类似于“漠不关心”的状态。     

Principals versus osmod: A comment on saito and otsu

Saito and Otsu (1988) compared their OSMOD method of nonmetric principal-component analysis to an early and incorrect implementation of the PRINCIPALS algorithm of Young, Takane, and de Leeuw (1978). In this comment we present results from the current, correct implementations of the algorithm.     

Factors influencing responding under multiple schedules of conditioned and unconditioned reinforcement

Two experiments examined pigeons' responses under multiple schedules of conditioned and unconditioned reinforcement. In one component, responses produced food according to a fixed-interval schedule; in a second component, responses produced brief stimuli according to a fixed-ratio schedule. When brief-stimulus presentations were paired with food in the first component, rates in the second component were usually higher than 10 responses per minute. When pairing in the first component was eliminated, responding continued to be maintained in the second component. Elimination of food presentation from the first component substantially decreased responding in the second component, even though the brief stimulus had not been paired with food. Experiment II demonstrated that response rate was affected by the duration of both the second component and the brief stimulus. The results suggest that three conditions are important in maintaining responding with brief-stimulus presentations: (1) pairing the brief stimulus, at least initially, with food, (2) maintaining unconditioned reinforcement in one component, and (3) employing optimal brief-stimulus and component durations.     

Some developments in multivariate generalizability

This article is concerned with estimation of components of maximum generalizability in multifacet experimental designs involving multiple dependent measures. Within a Type II multivariate analysis of variance framework, components of maximum generalizability are defined as those composites of the dependent measures that maximize universe score variance for persons relative to observed score variance. The coefficient of maximum generalizability, expressed as a function of variance component matrices, is shown to equal the squared canonical correlation between true and observed scores. Emphasis is placed on estimation of variance component matrices, on the distinction between generalizability- and decision-studies, and on extension to multifacet designs involving crossed and nested facets. An example of a two-facet partially nested design is provided.Appreciation is expressed to the Office of Research in Medical Education, University of Texas Medical Branch, for permitting use of their data.     

Principal component analysis of three-mode data by means of alternating least squares algorithms

A new method to estimate the parameters of Tucker's three-mode principal component model is discussed, and the convergence properties of the alternating least squares algorithm to solve the estimation problem are considered. A special case of the general Tucker model, in which the principal component analysis is only performed over two of the three modes is briefly outlined as well. The Miller & Nicely data on the confusion of English consonants are used to illustrate the programs TUCKALS3 and TUCKALS2 which incorporate the algorithms for the two models described.     

The extension of component analysis to four-mode matrices

A model for four-mode component analysis is developed and presented. The developed model, which is an extension of Tucker's three-mode factor analytic model, allows for the simultaneous analysis of all modes of a four-mode data matrix and the consideration of relationships among the modes. An empirical example based upon viewer perceptions of repetitive advertising shows the four-mode model applicable to real data.This research was supported by the University of Kansas School of Business Research Fund provided by the Fourth National Bank & Trust Company, Wichita. The ideas and opinions expressed herein are solely those of the author.     

Redundancy analysis an alternative for canonical correlation analysis

A component method is presented maximizing Stewart and Love's redundancy index. Relationships with multiple correlation and principal component analysis are pointed out and a rotational procedure for obtaining bi-orthogonal variates is given. An elaborate example comparing canonical correlation analysis and redundancy analysis on artificial data is presented.A Fortran IV program for the method of redundancy analysis described in this paper can be obtained from the author upon request.