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.     

Principal component analysis of three-mode data by means of alternating least squares algorithms

A new method to estimate the parameters of Tucker's three-mode principal component model is discussed, and the convergence properties of the alternating least squares algorithm to solve the estimation problem are considered. A special case of the general Tucker model, in which the principal component analysis is only performed over two of the three modes is briefly outlined as well. The Miller & Nicely data on the confusion of English consonants are used to illustrate the programs TUCKALS3 and TUCKALS2 which incorporate the algorithms for the two models described.     

The extension of component analysis to four-mode matrices

A model for four-mode component analysis is developed and presented. The developed model, which is an extension of Tucker's three-mode factor analytic model, allows for the simultaneous analysis of all modes of a four-mode data matrix and the consideration of relationships among the modes. An empirical example based upon viewer perceptions of repetitive advertising shows the four-mode model applicable to real data.This research was supported by the University of Kansas School of Business Research Fund provided by the Fourth National Bank & Trust Company, Wichita. The ideas and opinions expressed herein are solely those of the author.     

On the effects of component durations and component reinforcement rates in multiple schedules

Four experiments, each using the same six pigeons, investigated the effects of varying component durations and component reinforcement rates in multiple variable-interval schedules. Experiment 1 used unequal component durations in which one component was five times the duration of the other, and the shorter component was varied over conditions from 120 seconds to 5 seconds. The schedules were varied over five values for each pair of component durations. Sensitivity to reinforcement rate changes was the same at all component durations. In Experiment 2, both component durations were 5 seconds, and the schedules were again varied using both one and two response keys. Sensitivity to reinforcement was not different from the values found in Experiment 1. In Experiment 3, various manipulations, including body-weight changes, reinforcer duration changes, blackouts, hopper lights correlated with keylights, and overall reinforcement rate changes were carried out. No reliable increase in reinforcement sensitivity resulted from any manipulation. Finally, in Experiment 4, reinforcement rates in the two components were kept constant and unequal, and the component durations were varied. Shorter components produced significantly increased response rates normally in the higher reinforcement rate component, but schedule reversals at short component durations eliminated the response rate increases. The effects of component duration on multiple schedule performance cannot be interpreted as changing sensitivity to reinforcement nor to changing bias.     

ANOVA and ANCOVA of pre- and post-test,ordinal data

With random assignment to treatments and standard assumptions, either a one-way ANOVA of post-test scores or a two-way, repeated measures ANOVA of pre- and post-test scores provides a legitimate test of the equal treatment effect null hypothesis for latent variable . In an ANCOVA for pre- and post-test variablesX andY which are ordinal measures of and , respectively, random assignment and standard assumptions ensure the legitimacy of inferences about the equality of treatment effects on latent variable . Sample estimates of adjustedY treatment means are ordinal estimators of adjusted post-test means on latent variable .     

A BRIEF COMPONENT ANALYSIS OF POTENTIAL TREATMENT PACKAGES IN AN OUTPATIENT CLINIC SETTING WITH YOUNG CHILDREN

The purpose of this study was to develop outpatient clinic assessments that allowed us to assess multiple treatment variables, produce relatively quick effects, and isolate active treatment components. Assessment began by evaluating a treatment package consisting of antecedent and consequence variables followed by a component analysis to determine the separate effects of the treatment variables. Three examples of the findings are presented.     

The indirect effect of cognitive reserve on the relationship between age and cognition in pathological ageing: A cross-sectional retrospective study in an unselected and consecutively enrolled sample

Cognitive reserve (CR) allows individuals to maintain cognitive functionality even in the presence of pathologies. The compensation hypothesis suggests that CR plays an indirect role between age and cognitive decline, contrasting the negative effect of ageing on cognition. We test this hypothesis in an unselected and consecutively enrolled sample of memory clinic attendees (n = 134) who completed the CR Index questionnaire and three neuropsychological tests assessing global cognition (MMSE, FAB, CDT). Participants were divided into two groups based on standard diagnostic criteria (DSM-5): those who were cognitively impaired (n = 92) and those who were preserved (n = 42). A principal component analysis was used to extract a composite measure of global cognitive functioning from the three neuropsychological tests, and mediation analysis was used to examine the relationship between CR, age and global cognitive functioning in the two groups. Results revealed that: (i) age had a significant direct negative effect on the global cognitive score in both groups; (ii) the three socio-behavioural proxies of CR together suppress the direct negative relationship between age and global cognitive score in cognitively impaired patients but not in cognitively preserved participants. This study confirms the association between CR, age and cognition and allows us to validate its role in a population with cognitive impairment and extend findings to a low-to-middle educated population. These results hold important implications for public health and wellness promotion, emphasising the beneficial role of maintaining healthy and active physical, cognitive and social lifestyles.     

MPT模型在事件性前瞻记忆研究中的应用

前瞻性记忆是指对将要进行的活动或事件的记忆。前瞻记忆中,包含了前瞻成分和回溯成分。前人研究中,缺乏对前瞻成分和回溯成分有效的分离手段,使得对前瞻记忆机制的探讨缺乏深入挖掘。本文将MPT模型与Cohen等人的研究范式对比,分析了该模型在事件性前瞻记忆研究中的优势。文章对模型的理论基础,模型的主要内容,模型的数据计算方法,模型的效度以及模型的应用等几个方面进行了介绍,同时对模型使用中需要注意的问题进行了讨论。     

Teaching Principal Components Using Correlations

Introducing principal components (PCs) to students is difficult. First, the matrix algebra and mathematical maximization lemmas are daunting, especially for students in the social and behavioral sciences. Second, the standard motivation involving variance maximization subject to unit length constraint does not directly connect to the “variance explained” interpretation. Third, the unit length and uncorrelatedness constraints of the standard motivation do not allow re-scaling or oblique rotations, which are common in practice. Instead, we propose to motivate the subject in terms of optimizing (weighted) average proportions of variance explained in the original variables; this approach may be more intuitive, and hence easier to understand because it links directly to the familiar “R-squared” statistic. It also removes the need for unit length and uncorrelatedness constraints, provides a direct interpretation of “variance explained,” and provides a direct answer to the question of whether to use covariance-based or correlation-based PCs. Furthermore, the presentation can be made without matrix algebra or optimization proofs. Modern tools from data science, including heat maps and text mining, provide further help in the interpretation and application of PCs; examples are given. Together, these techniques may be used to revise currently used methods for teaching and learning PCs in the behavioral sciences.     

新颖语义联结形成的右半球优势效应

新颖语义联结形成是创造性思维的重要加工过程。采用谜题型歇后语为材料,直接操控语义联结的新颖性,通过两个实验考察汉语新颖语义联结形成的神经机制。实验1采用fMRI记录谜题型歇后语阅读理解过程的神经活动,结果显示相对于寻常语义关联条件,新颖语义关联条件更强地激活了右侧颞上回,该脑区可能与新颖语义信息的激活有关。实验2采用ERP技术在语义关联性判断任务中考察新颖语义联结形成神经加工的时空特征,结果显示相对于寻常语义关联条件,新颖语义关联条件在右侧颞区和右侧额区诱发了更正的晚期正成分,可能分别反映了新颖语义信息的激活以及选择与整合。研究结果支持了新颖语义联结形成的右半球加工优势效应。