Modeling item responses when different subjects employ different solution strategies

A model is presented for item responses when different subjects employ different strategies, but only responses, not choice of strategy, can be observed. Using substantive theory to differentiate the likelihoods of response vectors under a fixed set of strategies, we model response probabilities in terms of item parameters for each strategy, proportions of subjects employing each strategy, and distributions of subject proficiency within strategies. The probabilities that an individual subject employed the various strategies can then be obtained, along with a conditional estimate of proficiency under each. A conceptual example discusses response strategies for spatial rotation tasks, and a numerican example resolves a population of subjects into subpopulations of valid responders and random guessers.The first author's work was supported by Contract No. N00014-85-K-0683, project designation NR 150-539, from the Cognitive Science Program, Cognitive and Neural Sciences Division, Office of Naval Research. We are grateful to Murray Aitkin, Isaac Bejar, Neil Dorans, Frederiksen, and Marklyn Wingersky for their comments and suggestions, and to Alison Gooding, Maxine Kingston, Donna Lembeck, Joling Liang, and Kentaro Yamamoto for their assistance with Example 2.     

快速书写条件下硬笔笔迹变量与认知及个性特征的关系

以圆珠笔为书写工具．北京市某中学高一学生为被试,有效数据169人．探讨了在快速抄写条件下,笔迹书写特征与认知及个性的关系：18个笔迹变量可抽取笔压、结构、特征、字体和空间五个反映字的书写特征的因素;书写特征与认知因素间,横、竖笔压与概念形成速度。整篇压与视力追踪、字位与眼手协调相关显著;横笔压与16PF测验中的畏缩退怯——冒险敢为有正相关;竖笔压与艾森克个性因素的N有高相关。     

分时距认知特点的研究

本研究探讨了分时距估计的认知特点,检验了SS模型、PT模型和CS模型的预测效度,结果表明：分时距估计主要是在信息提取阶段采用分段推算策略对时间信息进行重建的过程,变化／分割和注意分配对分时距估计有显著影响;SS模型的预测效度最低,PT、CS模型的预测效度较高。     

小学儿童对习俗时间的周期性特点的认知

本研究探讨了小学儿童对习俗时间周期性特点的认知发展．实验任务是让被试判断两个给定日期之间的时间距离是正向接近还是反向接近。结果表明:儿童对习俗时间的周期性特点的认知成绩随年龄增长而不断提高;随着两个日期之间距离的增大,反应时不断增加,正确率不断降低,在两个日期相互接近的方向发生改变的边界处,反应时最长,正确率最低,表现出显著的“距离效应”和“边界效应”;儿童可以利用数字系统进行判断,他们的认知加工策略包括计数、数字运算和凭借习俗时间的空间表象进行模拟加工等等。     

Separability of item and person parameters in response time models

This paper discusses two forms of separability of item and person parameters in the context of response time (RT) models. The first is separate sufficiency: the existence of sufficient statistics for the item (person) parameters that do not depend on the person (item) parameters. The second is ranking independence: the likelihood of the item (person) ranking with respect to RTs does not depend on the person (item) parameters. For each form a theorem stating sufficient conditions, is proved. The two forms of separability are shown to include several (special cases of) models from psychometric and biometric literature. Ranking independence imposes no restrictions on the general distribution form, but on its parametrization. An estimation procedure based upon ranks and pseudolikelihood theory is discussed, as well as the relation of ranking independence to the concept of double monotonicity.I am indebted to Wim van der Linden for bringing Thissen's (1983) paper to my notice, and to Martijn Berger, Frans Tan, and the anonymous reviewers for their constructive comments on earlier drafts of this paper.     

Finite mixtures in confirmatory factor-analysis models

In this paper, various types of finite mixtures of confirmatory factor-analysis models are proposed for handling data heterogeneity. Under the proposed mixture approach, observations are assumed to be drawn from mixtures of distinct confirmatory factor-analysis models. But each observation does not need to be identified to a particular model prior to model fitting. Several classes of mixture models are proposed. These models differ by their unique representations of data heterogeneity. Three different sampling schemes for these mixture models are distinguished. A mixed type of the these three sampling schemes is considered throughout this article. The proposed mixture approach reduces to regular multiple-group confirmatory factor-analysis under a restrictive sampling scheme, in which the structural equation model for each observation is assumed to be known. By assuming a mixture of multivariate normals for the data, maximum likelihood estimation using the EM (Expectation-Maximization) algorithm and the AS (Approximate-Scoring) method are developed, respectively. Some mixture models were fitted to a real data set for illustrating the application of the theory. Although the EM algorithm and the AS method gave similar sets of parameter estimates, the AS method was found computationally more efficient than the EM algorithm. Some comments on applying the mixture approach to structural equation modeling are made.Note: This paper is one of the Psychometric Society's 1995 Dissertation Award papers.—EditorThis article is based on the dissertation of the author. The author would like to thank Peter Bentler, who was the dissertation chair, for guidance and encouragement of this work. Eric Holman, Robert Jennrich, Bengt Muthén, and Thomas Wickens, who served as the committee members for the dissertation, had been very supportive and helpful. Michael Browne is appreciated for discussing some important points about the use of the approximate information in the dissertation. Thanks also go to an anonymous associate editor, whose comments were very useful for the revision of an earlier version of this article.     

Exploring the set-theoretical structure of objects by additive trees

Arrangements of feature sets that have been proposed to represent qualitative and quantitative variation among objects are shown to generate identical sets of set-symmetric distances. The set-symmetric distances for these feature arrangements can be represented by path lengths in an additive linear tree. Imperfect versions of these feature arrangements are proposed, which also are indistinguishable by the set-symmetric distance model. The distances for the imperfect versions can be represented by path lengths in an additive imperfectly linear tree. When dissimilarities are defined by the more general contrast model and a constant may be added to proximity data, then for both the perfect and imperfect arrangements an additive tree analysis obtains a perfect fit with an imperfectly linear tree. However, in the case of the contrast model also the distinction between the perfect and imperfect arrangements disappears in that also for the perfect arrangements the resulting tree need no longer be linear.The author is grateful to Mathieu Koppen for detailed comments on an earlier version of this article.     

计量测验效度的一种方法——测量目标结构空间的实证性因素分析

该文提出了计量测验效度的一种统一方法。首先,根据测量目标由测验编制者提出一组可能的线性拟合模型,拟合模型的集合称作“测量目标结构空间”。然后运用实证性因素分析对各个假设的拟合模型进行多方面的拟合良好性检验。若其中的某一假设模型能最优地拟合预测资料,则该模型中的公共因素的方差总贡献与观测变量的总方差的比就可定义为该测验的效度     

教育因素对认知功能年老化过程的影响

应用言语－操作和人机对话两种方式共１２项作业,完成年龄和教育因素对认知功能影响的研究,被试共７３４人,４６－７５岁．结果表明：（１）年龄和教育因素对认知成绩的影响因作业而异,分别为年龄影响明显（图象自由回忆和无意义图形再认）、教育因素影响明显（卡片分类、图象分类和矩阵填图）、年龄和教育因素影响均明显（符号数字、词对联想学习、听觉和视觉数字广度）或均不明显（心算）．（２）四项非词语性作业速度明显受年龄和教育因素的双重影响．     

运用规则空间模型识别解题中的认知错误

运用规则空间模型识别学生解题中的认知错误,该模型将认知心理学,项目反应理论和数据库的代数理论相结合,将被试的二值反应模式映射为笛卡尔乘积空间的一组序偶,然后计算被试和错误规则在该空间的代表性位置之间的马氏距离,并通过贝叶斯决策准则划分被试的错误类型,根据６４４名中学生对３０个数学题目的反应,识别出其中８６％的学生可以被划分人１８种认知错误类型中。