Future-Oriented Job Analysis: A Description of the Process and Its Organizational Implications

An application of a future-oriented job analysis (FOJA) procedure used to gain an understanding of newly formed entry-level positions in a large insurance organization is described. A brief review of the relevant literature is presented to serve as a foundation upon which to consider the current FOJA procedure. Specific assumptions, stages, and results of the current procedure are detailed. The benefits of this application of FOJA are also discussed.     

Curry-Howard Terms for Linear Logic

In this paper we 1. provide a natural deduction system for full first-order linear logic, 2. introduce Curry-Howard-style terms for this version of linear logic, 3. extend the notion of substitution of Curry-Howard terms for term variables, 4. define the reduction rules for the Curry-Howard terms and 5. outline a proof of the strong normalization for the full system of linear logic using a development of Girard's candidates for reducibility, thereby providing an alternative to Girard's proof using proof-nets.     

检验能力对统计显著性检验的影响

利用计算机构造被试总体、模拟实验研究程序进行抽样研究,探讨抽样样本总体达到t检验显著性的数目与统计检验能力之间的一致性。模拟实验结果表明,统计检验能力与样本总体t检验显著性的数目具有很高的一致性,但两者同时受到显著性水平α、样本客量n和总体效果大小δ的影响,从而有可能影响统计推断的可靠性。因此,在进行显著性检验过程中,应对统计检验能力进行估计,这将有利于心理学研究成果的积累。     

Defense Mechanism Test (DMT) and Kernberg's theory of personality organization related to adolescents in psychiatric care

75 adolescent psychiatric patients were diagnosed with the perceptual projective test the Defense Mechanism Test (DMT) and also according to Kernberg's theory of personality organization (PO). The test protocols were scored in respect of 130DMT variables and analyzed by means of partial least squares (PLS) discriminant analysis. The objective was to try to separate the three types of PO, psychotic (PPO), borderline (BPO) and neurotic (NPO) by means of the DMT and also to compare the results with a similar study on adult psychiatric patients. The results showed that it is possible to separate significantly the three groups of PO. The BPO group seemed to be heterogeneous. The results were fairly similar to those obtained with adult psychiatric patients. The overall results supported the concurrent validity of Kernberg's theory of PO and for the DMT as well. The DMT seems to be a useful diagnostic method in respect of adolescent psychiatric patients.     

Iterated revision and minimal change of conditional beliefs

We describe a model of iterated belief revision that extends the AGM theory of revision to account for the effect of a revision on the conditional beliefs of an agent. In particular, this model ensures that an agent makes as few changes as possible to the conditional component of its belief set. Adopting the Ramsey test, minimal conditional revision provides acceptance conditions for arbitrary right-nested conditionals. We show that problem of determining acceptance of any such nested conditional can be reduced to acceptance tests for unnested conditionals. Thus, iterated revision can be accomplished in a virtual manner, using uniterated revision.     

阿拉伯数字与汉字大写数字认知的大脑功能一侧化实验研究

用半视野速示术检查阿拉伯数字和汉字大写数字在三种任务加工条件（认读、简单相加、奇偶概念异同判断）下进行认知的大脑两半球机能活动一侧化效应。结果表明：以被试正确反应的百分数为指标,两类数字的三种任务加工均没有表现出明显的视野（大脑半球）优势。以被试正确反应的反应时为指标,两类数字的认读和简单相加也未出现视野（大脑半球）的明显差别,而两类数字的奇偶概念异同判断却出现了差异显著的右视野（左半球）优势。     

Univariate repeated measures techniques applied to multivariate data

Repeated measures designs in psychology have traditionally been analyzed by the univariate mixed model approach, in which the repeated measures effect is tested against an error term based on the subject by treatment interaction. This paper considers the extension of this analysis to designs in which the individual repeated measures are multivariate. Sufficient conditions for a valid multivariate mixed model analysis are given, and a test is described to determine whether or not given data satisfy these conditions.     

Best linear prediction of composite universe scores

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. A general measurement procedure is described in which multiple test forms are developed from a table of specifications and each form is administered to a different sample of examinees. The measurement model categorizes items according to the cells of such a table, and the linear function derived for minimizing error variance in prediction uses responses to these categories. In addition, some distinctions are drawn between aspects of the approach taken here and the familiar regressed score estimates.The author thanks Robert L. Brennan, Michael J. Kolen, and Richard Sawyer for helpful comments and corrections, and anonymous reviewers for suggested improvements.     

An analytic comparison of Herrnstein's equations and a multivariate rate equation

Herrnstein's equations are approximations of the multivariate rate equation at ordinary rates of reinforcement and responding. The rate equation is the result of a linear system analysis of variable-interval performance. Rate equation matching is more comprehensive than ordinary matching because it predicts and specifies the nature of concurrent bias, and predicts a tendency toward undermatching, which is sometimes observed in concurrent situations. The rate equation contradicts one feature of Herrnstein's hyperbola, viz., the theoretically required constancy of k. According to the rate equation, Herrnstein's k should vary directly with parameters of reinforcement such as amount or immediacy. Because of this prediction, the rate equation asserts that the conceptual framework of matching does not apply to single alternative responding. The issue of the constancy of k provides empirical grounds for distinguishing between Herrnstein's account and a linear system analysis of single alternative variable-interval responding.     

Linear structural equations with latent variables

An interdependent multivariate linear relations model based on manifest, measured variables as well as unmeasured and unmeasurable latent variables is developed. The latent variables include primary or residual common factors of any order as well as unique factors. The model has a simpler parametric structure than previous models, but it is designed to accommodate a wider range of applications via its structural equations, mean structure, covariance structure, and constraints on parameters. The parameters of the model may be estimated by gradient and quasi-Newton methods, or a Gauss-Newton algorithm that obtains least-squares, generalized least-squares, or maximum likelihood estimates. Large sample standard errors and goodness of fit tests are provided. The approach is illustrated by a test theory model and a longitudinal study of intelligence.This investigation was supported in part by a Research Scientist Development Award (KO2-DA00017) and a research grant (DA01070) from the U. S. Public Health Service.