Empirical research on the identification of singular,multiple and subordinate argumentation

To examine to what degree argumentation skills are mastered by pupils who attend the vocational, general and academic streams in Dutch secondary education various subtests were constructed. The theoretical study of argumentation as exposed by Van Eemeren and Grootendorst was the basis for this test construction. In this article tests for the identification of singular, multiple and subordinate argumentation are described. Also an account is given of a pretest of these three subtests.     

汉字词特征语义提取的实验研究

本研究运用语义判断的方法,对汉字词特征语义的提取做了初步的探讨,被试是28名大学生。实验结果表明,汉字形声字的义符在汉字词定义特征语义提取中有重要作用,在义符与词义一致时,能加速词的定义特征语义的提取。义符对词的特有特征的语义提取无作用,而特有特征的强度能很好地预测提取时间。本研究还发现,词的熟悉性和该词距其上属的语义距离对词的定义特征的语义提取亦有重要影响。     

Category discrimination by pigeons using five polymorphous features

Eight pigeons were trained to discriminate between sets of color photographs of natural scenes. The scenes differed along five two-valued dimensions (site, weather, camera distance, camera orientation, and camera height), and all combinations of the feature values were used. One value of each dimension was designated as positive, and slides containing three or more positive feature values were members of the positive stimulus set. Thus, each feature had an equal, low, correlation with reinforcement, and all features had zero correlations with each other. Seven of the 8 pigeons learned this discrimination, and their responding came under the control of all five features. Within the positive and negative stimulus sets, response rates were higher to stimuli that contained more positive feature values. Once discrimination had been achieved, reversal training was given using a subset of the slides. In this subset, only a single feature was correlated with reinforcement. All pigeons learned this reversal successfully and generalized it to additional photographs with the same feature content. After reversal, the original reinforcement contingencies were reinstated, and training was continued using all the slides except those that had been used in reversal. Reversal generalized to these slides to some extent. Analysis of the response rates to individual slides showed that, compared with prereversal training, only the feature that had been subjected to reversal contingencies showed a reversed correlation with response rate. The remaining features showed the same correlation with response rate as they had before reversal training. Thus, reversal on some members of a category following category discrimination training led to generalization to stimuli within the category that were not involved in the reversal, but not to features that were not reversed. It is therefore inappropriate to refer to the pigeons as learning a concept.     

Some properties of estimated scale invariant covariance structures

Scale invariance is a property shared by many covariance structure models employed in practice. An example is provided by the well-known LISREL model subject only to classical normalizations and zero constraints on the parameters. It is shown that scale invariance implies that the estimated covariannce matrix must satisfy certain equations, and the nature of these equations depends on the fitting function used. In this context, the paper considers two classes of fitting functions: weighted least squares and the class of functions proposed by Swain.Constructive comments by the referees are greatly appreciated. The author gratefully acknowledges Michael Browne's interest in his work.     

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.     

Generalized Rough Sets (Preclusivity Fuzzy-Intuitionistic (BZ) Lattices)

The standard Pawlak approach to rough set theory, as an approximation space consisting of a universe U and an equivalence (indiscernibility) relation R U x U, can be equivalently described by the induced preclusivity ("discernibility") relation U x U \ R, which is irreflexive and symmetric.We generalize the notion of approximation space as a pair consisting of a universe U and a discernibility or preclusivity (irreflexive and symmetric) relation, not necessarily induced from an equivalence relation. In this case the "elementary" sets are not mutually disjoint, but all the theory of generalized rough sets can be developed in analogy with the standard Pawlak approach. On the power set of the universe, the algebraic structure of the quasi fuzzy-intuitionistic "classical" (BZ) lattice is introduced and the sets of all "closed" and of all "open" definable sets with the associated complete (in general nondistributive) ortholattice structures are singled out.The rough approximation of any fixed subset of the universe is the pair consisting of the best "open" approximation from the bottom and the best "closed" approximation from the top. The properties of this generalized rough approximation mapping are studied in the context of quasi-BZ lattice structures of "closed-open" ordered pairs (the "algebraic logic" of generalized rough set theory), comparing the results with the standard Pawlak approach. A particular weak form of rough representation is also studied.     

整体汉字字形识别过程探索

本研究用微观发生范式探索了整体汉字和人工字的字形识别过程 ,主要获得以下结果 :1真字和人工字的正确提取率随呈现时间增长而提高 ,字形刺激的特征提取是一个有序的发展过程 ,字形识别加工受字特性 (真字与人工字 )和笔划数因素影响。2在以“十”为骨架和以“囗”为包围结构的字刺激中经常首先提取“十”或“囗”,而且首特征“十”或“囗”的提取不受字形熟悉性影响 ;笔划数变量仅对含“十”特征的字刺激的首特征提取产生影响。3在以上两类汉字中 ,“十”或“囗”作为首特征提取促进了字形识别加工过程。     

A note on the investigation of local and global identifiability

In general, nonlinear models such as those commonly employed for the analysis of covariance structures, are not globally identifiable. Any investigation of local identifiability must either yield a mapping of identifiability onto the entire parameter space, which will rarely be feasible in any applications of interest, or confine itself to the neighbourhood of such points of special interest as the maximum likelihood point.The author would like to thank J. Jack McArdle and Colin Fraser for their comments on this paper.     

发展性阅读障碍的听觉时间加工缺陷

发展性阅读障碍是指个体在智力正常并且不缺乏学校教育的情况下, 仍无法获得与年龄相匹配的阅读技能的一种学习障碍, 其缺陷的本质一直是研究者争论的焦点。大量研究显示, 阅读障碍者常表现出听觉时间加工损伤。在行为层面, 阅读障碍者难以辨别快速、连续呈现刺激的顺序以及刺激本身的动态时间特征。在神经层面, 阅读障碍者诱发的失匹配负波更弱且具有异常的神经同步加工。这些损伤同时存在于对言语和非言语刺激的加工中, 表明听觉时间加工缺陷非言语加工所特有。未来的研究还需阐明以下几个问题：1)阅读障碍的听觉时间加工缺陷发生在哪些时间窗口, 随年龄增长如何变化; 2)阅读障碍听觉时间加工缺陷在神经层面的时间进程是怎样的; 3)听觉时间加工缺陷是否为阅读障碍的核心缺陷。