基于概化理论的方差分量变异量估计

概化理论广泛应用于心理与教育测量实践中, 方差分量估计是进行概化理论分析的关键。方差分量估计受限于抽样, 需要对其变异量进行探讨。采用蒙特卡洛(Monte Carlo)数据模拟技术, 在正态分布下讨论不同方法对基于概化理论的方差分量变异量估计的影响。结果表明: Jackknife方法在方差分量变异量估计上不足取; 不采取Bootstrap方法的“分而治之”策略, 从总体上看, Traditional方法和有先验信息的MCMC方法在标准误及置信区间这两个变异量估计上优势明显。     

一种基于Rasch模型的Angoff方法及其应用

水平厘定方法在近二十年来发展迅速,其中Angoff方法的应用最为广泛。该文在已有的方法上提出了一种基于Rasch模型的改进的Angoff方法,该方法使用Rasch模型来估计典型学生的位置,通过均方残差等方法剔除不一致的裁判。文章最后详细阐述了该方法在香港全港性系统评估中的应用。     

用Delta法估计多维测验合成信度的置信区间

大量研究表明,一般情况下用合成信度可以较好地估计测验信度。对于合成信度及其置信区间的估计方法,在单维测验的情形已有不少研究。但罕有研究讨论多维测验合成信度的区间估计方法。本文用Delta法推导出计算多维测验合成信度的标准误公式,进而计算置信区间,并用一个例子说明如何编程估计多维测验合成信度及其置信区间。     

近五年来《心理学报》与《心理科学》文献计量比较研究

该研究采用文献计量学方法,以2005—2009年《心理学报》与《心理科学》的载文为研究对象,分别统计了两种期刊载文的研究领域、研究方法、载文体裁和作者特征等方面的数据信息。结果发现：基础领域是两种期刊心理学研究的主要领域;在应用领域方面两种期刊侧重点不同;两种期刊在研究方法的选择上是一致的,即实验法是心理学研究的主要研究方法,数据的搜集则主要靠测评法;两种期刊在心理学研究者的地区分布中都出现了明显的地区优势,优势地区与核心作者群略有不同。     

Some multiple correlation and predictor selection methods

The Doolittle, Wherry-Doolittle, and Summerfield-Lubin methods of multiple correlation are compared theoretically as well as by an application in which a set of predictors is selected. Wherry's method and the Summerfield-Lubin method are shown to be equivalent; the relationship of these methods to the Doolittle method is indicated. The Summerfield-Lubin method, because of its compactness and ease of computation, and because of the meaningfulness of the interim computational values, is recommended as a convenient least squares method of multiple correlation and predictor selection.     

A method of score conversion through item statistics

A method is presented for converting the scores on one form of a test to those on another form of the same test. The method is particularly applicable to the case where each form has been administered to a different group and the only link between the two forms is a subset of items common to both. The proposed method, called theitem method of conversion, has been applied to several tests for which other methods of conversion are available for comparison. The necessary data are limited to tests for which the total score is the criterion for item analyses. The method gives highly satisfactory results for all the tests to which it has been applied, particularly when the two groups are rather different, in which case the delta method (a different item method) is inappropriate.The authors are only two of a group, including W. H. Angoff, F. M. Lord, and M. K. Schultz, all of whom have made important contributions to this paper.     

青少年未来取向三种测试途径的比较

考察未来取向测试新方法（作品分析法）有效性及对比已有测量方法(自陈问卷法、行为测试法)的优缺点。结果发现,问卷法测得青少年未来取向水平随年龄增长逐渐降低,行为测试法和作品分析法测得青少年未来取向水平随年龄增长逐渐提高;问卷法测得未来取向与学校投入相关密切,行为测试法测得未来取向与学业成绩相关密切,作品分析法测得未来取向与学校投入、学业成绩均相关。作品分析法是一种有效测量青少年未来取向的新途径。     

A comparison of the thurstone method of multiple factors with the hotelling method of principal components

The factors found by the Hotelling method of principal components present the same necessity for rotation as those found by the Thurstone method of multiple factors.The Thurstone method of multiple factors is here found superior to the Hotelling method of principal components, and is suggested as the method of choice for all problems requiring the determination of elemental components from a group of related variables, since it was found on every point of comparison that, when applied to a correlation matrix of unknown communalities, the Thurstone method was more accurate than the Hotelling method, and also required much less time.     

Multidimensional scaling of individual differences for an individual person with a hand-held calculator

An extension to the INDSCAL method of individual differences scaling was developed. The method derives measures of deviation from a “standard” observer, who is defined in terms of the INDSCAL subject weights. These weights are calculated for one individual person at a time. The method is implemented in a small hand-held calculator. The calculator is used for data acquisition, and it interacts with the user in a conversational manner through an alpha-numeric display. The present implementation of the method scales 84 judgments of pair similarity among seven objects and derives subject weights on two dimensions. The method can be extended to sets of up to 16 objects and up to six dimensions. The method is a feasible, cost-effective approach to classification of individuals on complex perceptual attributes within a single 1-h session.     

概化理论方差分量估计的跨分布分析

方差分量估计是进行概化理论分析的关键。采用MonteCarlo模拟技术,探讨心理与教育测量数据分布对概化理论各种方法估计方差分量的影响。数据分布包括正态、二项和多项分布,估计方法包括Traditional、Jackknife、Bootstrap和MCMC方法。结果表明:(1)Traditional方法估计正态分布和多项分布数据的方差分量相对较好,估计二项分布数据需要校正,Jackknife方法准确地估计了三种分布数据的方差分量,校正的Bootstrap方法和有先验信息的MCMC方法(MCMCinf)估计三种分布数据的方差分量结果较好;(2)心理与教育测量数据分布对四种方法估计概化理论方差分量有影响,数据分布制约着各种方差分量估计方法性能的发挥,需要加以区分地使用。     

Geometric vector orthogonal rotation method in multiple-factor analysis

An objective method for the orthogonal rotation of factors which gives results closer to the graphic method is proposed. First, the fact that the varimax method does not always satisfy simple-structure criteria, e.g., the positive manifold and the level contributions of all factors, is pointed out. Next, the principles of our method which are based on “geometric vector” are discussed, and the computational procedures for this method are explained using Harman and Holzinger's eight physical variables. Finally, six numerical examples by our method are presented, and it is shown that they are very close to the factors obtained from empirical studies both in values and in signs.     

How to avoid the fallacies of cognitive subtraction in brain imaging

Functional neuroanatomy of cognitive processes is generally derived by subtraction of a control task from an experimental task. We show that this method is logically untenable and propose to replace it with an adaptation of the specific-effect method and of the additive-factor method. The basic flaw that undermines the subtractive method is the comparison between different tasks. We argue that the specific-effect method should be used when investigating activations produced by different levels of a qualitative variable, whereas the additive-factor method should be used for quantitative variables. The use of these methods allows one to distinguish between parallel and serial stages of processing and between local and distributed processing.     

A non-graphical method for transforming an arbitrary factor matrix into a simple structure factor matrix

The most commonly used method of factoring a matrix of intercorrelations is the centroid method developed by L. L. Thurstone. It is, however, necessary to transform the centroid matrix of factor loadings into a simple structure matrix in order to facilitate the interpretation of the factor loadings. Current methods for effecting this transformation are chiefly graphical and require considerable experience and personal judgment. This paper presents a new method for transforming an arbitrary factor matrix into a simple structure matrix by methods almost completely objective. The theory underlying the method is developed and approximation procedures are derived. The method is applied to a matrix of factor loadings previously analyzed by Thurstone.     

Dual imputation model for incomplete longitudinal data

Missing values are a practical issue in the analysis of longitudinal data. Multiple imputation (MI) is a well‐known likelihood‐based method that has optimal properties in terms of efficiency and consistency if the imputation model is correctly specified. Doubly robust (DR) weighing‐based methods protect against misspecification bias if one of the models, but not necessarily both, for the data or the mechanism leading to missing data is correct. We propose a new imputation method that captures the simplicity of MI and protection from the DR method. This method integrates MI and DR to protect against misspecification of the imputation model under a missing at random assumption. Our method avoids analytical complications of missing data particularly in multivariate settings, and is easy to implement in standard statistical packages. Moreover, the proposed method works very well with an intermittent pattern of missingness when other DR methods can not be used. Simulation experiments show that the proposed approach achieves improved performance when one of the models is correct. The method is applied to data from the fireworks disaster study, a randomized clinical trial comparing therapies in disaster‐exposed children. We conclude that the new method increases the robustness of imputations.     

内隐记忆研究的实验方法探索：启动效应计量方法的改进思路及其实验研究

以实验鉴定了常规的启动效应计量方法的有效性程度,并为客观地计量启动效应,创用了“超意识广度法”、“二次比较法”等．结果发现：（１）如被试数量较少,以不同补笔率为“基线值”所求得的启动效应之间发生显著差异的可能性存在;（２）超意识广度法能克服“阈下呈现刺激法”“分散注意法”的不足,为内隐记忆提供有利的识记情境;（３）“二次比较法”能为正常人内隐记忆的存在提供更为直接、可靠的证据,并能客观、精确地计量启动效应。     

Estimation of the correlation coefficient in contingency tables with possibly nonmetrical characters

A method of estimating the product moment correlation from the polychoric series is developed. This method is shown to be a generalization of the method which uses the tetrachoric series to obtain the tetrachoric correlation. Although this new method involves more computational labor, it is shown to be superior to older methods for data grouped into a small number of classes.     

校正的Bootstrap方法对概化理论方差分量及其变异量估计的改善

Bootstrap方法是一种有放回的再抽样方法, 可用于概化理论的方差分量及其变异量估计。用Monte Carlo技术模拟四种分布数据, 分别是正态分布、二项分布、多项分布和偏态分布数据。基于p×i设计, 探讨校正的Bootstrap方法相对于未校正的Bootstrap方法, 是否改善了概化理论估计四种模拟分布数据的方差分量及其变异量。结果表明：跨越四种分布数据, 从整体到局部, 不论是“点估计”还是“变异量”估计, 校正的Bootstrap方法都要优于未校正的Bootstrap方法, 校正的Bootstrap方法改善了概化理论方差分量及其变异量估计。     

自适应分组认知诊断测验设计及其选题策略

应用OMST在线装配模式,提出自适应分组认知诊断测验（CD-AMGT）。由于知识状态的先决关系是偏序关系,而且构成格（lattice),利用知识状态当前估计值在格中的上下确界对被试真实知识状态的可能范围进行界定,由此装配下一分组,分组中结合PWKL策略或SHE策略进行选题以兼顾诊断精度、效率和安全性。模拟实验表明,CD-AMGT与PWKL、SHE对比,当题目类型丰富时,以分类准确率略微降低为代价,其题库使用均匀性和计算用时均表现出较大优势。     

A new horizontal eye movement calibration method: Subject-controlled “smooth pursuit” and “zero drift”

A subject-controlled smooth pursuit method of calibration of eye movement apparatus is proposed for the horizontal axis which is more rapid, requires no interpolation and no linearity assumption, and is as accurate as the fixation point method usually used. The zero drift method of verification proposed then permits accuracy to be estimated in a way that distinguishes apparatus errors from fixation errors. This is only possible in the fixation point method by asking the subject to make repeated long fixations.     

CD-CAT初始阶段项目选取方法

CD-CAT是CDA同CAT的相结合的产物,适用于课堂教学,是教师补救教学、学生自我学习的重要工具。作为CD-CAT重要组成部分的初始阶段项目选取方法是影响测验判准率的重要因素。本文基于现有研究和CDA的项目区分度提出了四种新的初始阶段项目选取方法:CTTID法、CDI法、CTTIDR*法和CDIR*法。通过模拟研究发现,在定长的CD-CAT下,题库质量是HD-HV下,初始阶段结束时,CTTIDR*法的PCCR比现有的T阵法高了.2999,比PWKL高了.1707,其它题库下趋势相同。整个测验结束时CTTIDR*法的判准率仍然是最高的。在变长的CD-CAT下,最大后验概率大于.7、.8、.9下,CTTIDR*法的被试平均测验长度比T阵法分别缩短了2.6170、2.2347、1.7470道题。