Delay and number of food reinforcers: Effects on choice and latencies

Pigeons were given a choice between two identical-duration situations (terminal links of chain schedules). One terminal link of the choice pair provided two food deliveries, and the other provided five. The exact times of these food deliveries differed between the terminal links and were varied over conditions. A single response during the initial link gave immediate access to the corresponding terminal link. Forced trials, during which only one of the initial-link keys was lighted, were interspersed with choice trials during which both initial-link keys were lighted. Choice tended to favor whichever terminal link was correlated with the higher sum of the immediacies (i.e., the sum of the reciprocals of the delays to each of the reinforcers following the choice, with all delays measured from the choice). Latencies on forced trials and on choice trials also were related (negatively) to the sum of the immediacies. This correlation among response measures (choice and latencies) suggests that both measures are manifestations of the effect of conditioned reinforcement on response tendencies.     

Noniterative estimation and the choice of the number of factors in exploratory factor analysis

Based on the usual factor analysis model, this paper investigates the relationship between improper solutions and the number of factors, and discusses the properties of the noniterative estimation method of Ihara and Kano in exploratory factor analysis. The consistency of the Ihara and Kano estimator is shown to hold even for an overestimated number of factors, which provides a theoretical basis for the rare occurrence of improper solutions and for a new method of choosing the number of factors. The comparative study of their estimator and that based on maximum likelihood is carried out by a Monte Carlo experiment.The author would like to express his thanks to Masashi Okamoto and Masamori Ihara for helpful comments and to the editor and referees for critically reading the earlier versions and making many valuable suggestions. He also thanks Shigeo Aki for his comments on physical random numbers.     

MODIFYING LETTER AND NUMBER REVERSALS IN ELEMENTARY SCHOOL CHILDREN1

Children from regular and special-education classes were exposed to tutoring procedures designed to modify letter and number reversals. In Experiment I, two students showed reversals during letter-naming (e.g., saying p for q) and two-digit number (e.g., writing 31 for 13) exercises. In Experiment II, one subject made two-digit reversals, while the other child reversed single-digit numbers (e.g., 9 written with circle on right side of stem). The subject in Experiment III emitted letter reversals under naming, dictation, and copying exercises. The child in Experiment IV showed written letter reversals on both sides of the “body midline” under dictation procedures. Basic treatment procedures during all experiments involved modelling of correct and incorrect symbol formation, and differential experimenter feedback following student responses. During Experiments I and II, subjects were praised for each correct response, and informed when a reversal occurred. Experiment III included a Modelling Only Phase before these feedback procedures. Besides praise, treatment conditions in Experiment IV consisted of additional feedback following correct responses (e.g., charting correct responses), and temporal delays imposed between dictated letters and student responses. Except for occasional letter-naming reversals of one subject (Experiment I), and letter dictation errors of another (Experiment IV), reversals were eliminated when all experiments terminated. The Modelling Only Phase in Experiment III also reduced reversals to a low level. These findings suggest that a variety of reversal problems may be effectively assessed and remediated via simple modelling and reinforcement procedures. In addition, postcheck observations indicated that the effects were enduring. The present procedures should be easily implemented by school personnel.     

FACAIC: Model selection algorithm for the orthogonal factor model using AIC and CAIC

This paper describes the authors' FORTRAN algorithm FACAIC for choosing the number of factors for an orthogonal factor model using Akaike's Information Criterion. FACAIC utilizes the IMSL subroutine OFCOMM.The authors dedicate this algorithm to Professor Hirotugu Akaike in appreciation of his pioneering work on AIC which was originally intended for the factor analysis and other statistical model identification problems.     

4～5岁儿童对书面数符号的表征和理解能力的发展

本研究对61名中班儿童的书面数符号表征和理解能力进行了跟踪调查。一年中三次个别面试的结果表明,约40％的4岁儿童已能运用1—10的书面数符号表征数量。至中班末期,大多数5岁儿童能够较熟练地运用至少1一17的书面数符号来表征数量,尽管其中有人在两位数的表征和数字的正确写法上有困难。儿童的书面数符号表征与他们的基数概念发展水平密切相关。大学附属幼儿园4—5岁儿童的书面数符号表征能力好于为工人家庭服务的幼儿园儿童的能力。     

Evaluating the Sampling Performance of Exploratory and Cross-Validated DETECT Procedure with Imperfect Models

Among the methods proposed for identifying the number of latent traits in multidimensional IRT models, DETECT has attracted the attention of both methodologists and applied researchers as a nonparametric counterpart to other procedures. The current study investigated the overall performance of the DETECT procedure and its outcomes using a real-data sampling design recommended by MacCallum (2003 MacCallum, R.C. (2003). Working with imperfect models. Multivariate Behavioral Research, 38 (1), 113–139. http://dx.doi.org/10.1207/S15327906MBR3801_5[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and compared the results from a purely simulated data set that was generated with a well-specified “perfect” model. The comparison revealed that the sampling behavior of the maximized DETECT value and R-ratio statistics was quite robust to minor factors and other model misspecifications that potentially exist in the real data set, as there were negligible differences between the results of the real and simulated data sets. Item classification accuracy was also nearly identical for the real and simulated data sets. The accuracy of the identified number of dimensions reported by DETECT was the only outcome with an obvious difference between the purely simulated data set and the real data set. While the difference was small for smaller sample sizes, the identified number of dimensions was more accurate for larger sample sizes when the population data set was purely simulated. In many instances, exploratory DETECT analysis outperformed the cross-validated DETECT analysis in terms of overall accuracy.     

执行功能与数量加工：回顾与展望

回顾了执行功能与数量加工之间的复杂关系。其中,执行功能的4个子系统——抑制、转换、刷新和双任务协调对数量加工的影响各不相同：抑制可以在一定程度上改变数量加工时的自动激活程度;转换功能则主要依赖注意来进行调节;刷新与数量加工关系的研究成果比较少;而双任务协调与数量加工之间的联系存在争论。文章最后分3个方面进行了研究趋势的展望,认为未来执行功能与数量加工的研究将突破相关研究的局限,通过更精巧的设计和大量特殊被试的研究取得突破性进展。     

多级评分聚类诊断法的影响因素

从测验和被试两个层面探讨了属性数目、属性层级关系、被试知识状态分布、属性层级误设和Q矩阵误设等因素对GRCDM的影响, 以进一步考察GRCDM的特性。研究发现：(1)GRCDM对属性数目无依赖, 随属性数目的增多判准率反而增高; (2)被试知识状态分布对GRCDM判准率高低无影响; (3)属性层级误设对GRCDM的影响与属性层级类型有关, 当属性层级为无结构型和发散型时, “属性层级关系错乱”的判准率降幅最大; (4)Q矩阵误设对GRCDM的影响因层级关系而异, 收敛型和发散型受影响较小, 无结构型和线型的判准率在属性既冗余又缺失时降幅最大。     

汉字加工的基本单元:来自笔画数效应和部件数效应的证据

用命名作业和真假字判断作业考察了笔画数和部件数对汉字加工的影响,发现,当部件数保持恒定时,笔画数少的汉字较笔画数多的汉字加工快,这种笔画数效应和字频之间不存在交互作用;当笔画数被控制时,部件数效应也存在,但和字频有交互作用,表现在低频少部件汉字的加工要快于低频多部件汉字的加工,而高频汉字中的部件数效应不显著。实验还发现独体字（只有一个部件）的加工和合体字（部件数大于等于二）的加工有差异。作者认为,汉字的加工要经过笔画、部件和整字三个层次,其中单位部件的笔画数和部件数影响着汉字加工时间