The role of observing and attention in establishing stimulus control.

Early theorists (Skinner, Spence) interpreted discrimination learning in terms of the strengthening of the response to one stimulus and its weakening to the other. But this analysis does not account for the increasing independence of the two performances as training continues or for increases in control by dimensions of a stimulus other than the one used in training. Correlation of stimuli with different densities of reinforcement produces an increase in the behavior necessary to observe them, and greater observing of and attending to the relevant stimuli may account for the increase in control by these stimuli. The observing analysis also encompasses errorless training, and the selective nature of observing explains the feature-positive effect and the relatively shallow gradients of generalization generated by negative discriminative stimuli. The effectiveness of the observing analysis in handling these special cases adds to the converging lines of evidence supporting its integrative power and thus its validity.     

Estimation of stimulus-response curves by bayesian least squares

Bayesian least squares techniques are adapted to estimation of stimulus-response curves, rather broadly conceived. Illustrative examples deal with estimation of person characteristic curves and item characteristic curves in the context of mental testing, and estimation of a stimulus-response curve using data from a psychophysical experiment.The present paper is a version of an invited address of the same title, presented to the meetings of The Psychometric Society in Monterey, California on June 8, 1979, expanded by adding Example 1.The writer gratefully acknowledges the benefit of conversations with Don Pierce, and with John Shih, whose related work on density estimation pointed up an error in the original version of Section 2. He acknowledges, gratefully, support by the National Science Foundation through Grants MCS 76-02166A01 and MCS 78-01932. And he wishes to express his gratitude for the cordial hospitality and gracious cooperation offered by Professor Donald M. MacKay and the staff of the Department of Communication, University of Keele, during spring and summer, 1976; in particular, by Professor Dennis P. Andrews and Keichi Uchikawa, who kindly furnished data, a small portion of which is used in the illustrative example, Example 2.     

Orthomax rotation and perfect simple structure

A loading matrix has perfect simple structure if each row has at most one nonzero element. It is shown that if there is an orthogonal rotation of an initial loading matrix that has perfect simple structure, then orthomax rotation with 0 1 of the initial loading matrix will produce the perfect simple structure. In particular, varimax and quartimax will produce rotations with perfect simple structure whenever they exist.     

消费行为研究中的联合分析法

联合分析(Conjoint Analysis)是一种定量的研究消费者选择偏好的方法。虽然从它诞生到现在只有40年的历史,但它对消费者行为学的影响很大,它的发展更是日新月异。文章首先介绍了联合分析的基本概念,然后重点阐述了联合分析的原理、步骤和发展历程,最后对联合分析的发展方向作了一个简要概括。     

A General Approach for Fitting Pure Exploratory Bifactor Models

This article proposes a procedure for fitting a pure exploratory bifactor solution in which the general factor is orthogonal to the group factors, but the loadings on the group factors can satisfy any orthogonal or oblique rotation criterion. The proposal combines orthogonal Procrustes rotations with analytical rotations and consists of a sequence of four steps. The basic input is a semispecified target matrix that can be (a) defined by the user, (b) obtained by using Schmid-Leiman orthogonalization, or (c) automatically built from a conventional unrestricted solution based on a prescribed number of factors. The relevance of the proposal and its advantages over existing procedures is discussed and assessed via simulation. Its feasibility in practice is illustrated with two empirical examples in the personality domain.     

Matfit: A fortran subroutine for comparing two matrices in a subspace

This research was supported by grant APA 3020 from the Natural Sciences and Engineering Research Council of Canada. The author would like to thank Dr. David O'Hare for providing the data used to illustrate the use of the program MATFIT.     

A note on identification in the oblique and orthogonal factor analysis models

Conditions for removing the indeterminancy due to rotation are given for both the oblique and orthogonal factor analysis models. The conditions indicate why published counterexamples to conditions discussed by Jöreskog are not identifiable.The author would like to thank Gordon Bechtel and the reviewers for their comments and suggestions.     

多种因素对时间连续阈限的影响

该研究做了两个实验,研究了七个因素——刺激的类型、刺激的复杂度、刺激的强度、刺激的呈现时间、被试对两刺激的判断标准、同一种感觉道的个数、性别——对时间连续阈限的影响.在实验一中,结果表明,刺激的类型、刺激的呈现时间、被试对两刺激的判断标准和同一种感觉道的个数四个因素对时间连续阈限有显著影响,而刺激的复杂度、刺激的强度和性别三个因素对时间连续阈限没有显著影响。在实验二中,结果表明,在影响显著的四个因素之间不存在交互作用。     

Relationship of Inglehart's and Schwartz's value dimensions revisited

This study examines the relationship between Inglehart's and Schwartz's value dimensions—both at the individual and the country levels. By rotating one set of items towards the other, we show that these value dimensions have more in common than previously reported. The ranking of countries (N = 47) based on Schwartz's Embeddedness—Autonomy and the Survival—Self‐Expression dimensions reached a maximum of similarity, r = .82, after rotating Inglehart's factor scores 27 degrees clockwise. The correlation between the other pair of dimensions (Schwartz's Hierarchy‐Mastery—Egalitarianism‐Harmony and Inglehart's Traditional—Secular‐Rational values) was near zero before and after rotation. At the individual level (N = 46,444), positive correlations were found for Schwartz's Conservation—Openness dimension with both of Inglehart's dimensions (Survival—Self‐Expression and Traditional—Secular‐Rational values). The highest correlation with this Schwartz dimension was obtained at the Secular‐Rational/Self‐Expression diagonal, r = .24, after rotating the factor scores 45 degrees clockwise. We conclude that Schwartz's and Inglehart's originally proposed two‐dimensional value structures share one dimension at the country level and some commonality at the individual level, whereas the respective other pair of dimensions seem to be more or less unrelated.