Reliability and expected loss: A unifying principle

We provide a unified, theoretical basis on which measures of data reliability may be derived or evaluated, for both quantitative and qualitative data. This approach evaluates reliability as the proportional reduction in loss (PRL) that is attained in a sample by an optimal estimator. The resulting measure is between 0 and 1, linearly related to expected loss, and provides a direct way of contrasting the measured reliability in the sample with the least reliable and most reliable data-generating cases. The PRL measure is a generalization of many of the commonly-used reliability measures.We show how the quantitative measures from generalizability theory can be derived as PRL measures (including Cronbach's alpha and measures proposed by Winer). For categorical data, we develop a new measure for the general case in which each of N judges assigns a subject to one of K categories and show that it is equivalent to a measure proposed by Perreault and Leigh for the case where N is 2.Bruce Cooil is an Associate Professor of Statistics, and Roland T. Rust is a Professor and area head for Marketing. The authors thank three anonymous reviewers and an Associate Editor for their helpful comments and suggestions. This work was supported in part by the Dean's Fund for Faculty Research of the Owen Graduate School of Management, Vanderbilt University.     

字频在直接和间接记忆测验中的比较研究

本研究通过3×2×2混合设计实验,比较了字频在即刻和第5天两种施测时间下的两类记忆测验中的不同作用。本研究支持了词汇通达搜索模型对宇频作用机制的分析及传输适当认知程序观点对实验性分离现象的解释,并发现外显记忆与内隐记忆都会发生遗忘,但原因可能并不相同,而且字频影响两类记忆的遗忘进程。     

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.     

On structural models for analyzing change

The recommendation to base the analysis of multi-wave data upon explicit models for change is advocated. Several univariate and multivariate models are described, which emerge from an interaction between the classical test theory and the structural equation modeling approach. The resulting structural models for analyzing change reflect in some of their parameters substantively interesting aspects of intra- and interindividual change in follow-up studies. The models are viewed as an alternative to an ANOVA-based analysis of longitudinal data, and are illustrated on data from a cognitive intervention study of old adults (Bakes et al , 1986). The approach presents a useful means of analyzing change over time, and is applicable for purposes of (latent) growth curve analysis when analysis of variance assumptions are violated (e.g., Schaie & Hertzog, 1982; Morrison, 1976).     

运动竞赛焦虑量表中国常模的修订

运动竞赛焦虑量表是由美国的马腾斯专为运动员编制的特质焦虑量表。它是一种与特定的情境相结合的、能够有效地测出被测者通常在运动竞赛(或游戏)时焦虑水平的量表。我们在全国六大区十四个省市抽取了2,988名被试,修订了10—12岁(男、女),13—15岁(男、女),16—18岁(男、女)和19—25岁(男、女)的八个常模。同时,进行了效度和信度检验。本量表可以作为对业余的或专业的运动员进行运动竞赛焦虑的诊断与研究用。     

On the relation between demographic variables and neuropsychological test performance

This paper reports a study of the relation between demographic variables and neuropsychological test performance in a sample of 141 normal subjects. A preliminary analysis demonstrated the importance of age, educational level, sex, and Verbal IQ for the prediction of neuropsychological test performance. The main study is a detailed analysis of the relation between these four variables and neuropsychological test performance. The results are presented in the form of standardized regression coefficients and are discussed in relation to the problem of predicting expected premorbid performance in neuropsychological tests.     

Classical test theory based and factor analytic structural models for analyzing change: A note on differences and similarities

This note is concerned with differences and similarities between structural models for analyzing change, which are conceptualized within two different modelling traditions: the one based on the classical test theory, and that within the factor-analytic approach. It is shown that these two possibilities lead to models for studying change, which are indistinguishable when using for data analytic purposes structural modeling programs, such as LISREL, EQS, COSAN, LISCOMP, RAMONA, EzPATH, SAS PROC CALIS. The reason for this data-analytic equivalence of the two conceptually different types of models is the confounding of their differences in the corresponding implied covariance matrix structures.     

A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF

A model-based modification (SIBTEST) of the standardization index based upon a multidimensional IRT bias modeling approach is presented that detects and estimates DIF or item bias simultaneously for several items. A distinction between DIF and bias is proposed. SIBTEST detects bias/DIF without the usual Type 1 error inflation due to group target ability differences. In simulations, SIBTEST performs comparably to Mantel-Haenszel for the one item case. SIBTEST investigates bias/DIF for several items at the test score level (multiple item DIF called differential test functioning: DTF), thereby allowing the study of test bias/DIF, in particular bias/DIF amplification or cancellation and the cognitive bases for bias/DIF.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-90-J-1940, 4421-548 and National Science Foundation Mathematics Grant NSF-DMS-91-01436. The research reported here is collaborative in every respect and the order of authorship is alphabetical. The assistance of Hsin-hung Li and Louis Roussos in conducting the simulation studies was of great help. Discussions with Terry Ackerman, Paul Holland, and Louis Roussos were very helpful.     

Equivalent models in covariance structure analysis

Defining equivalent models as those that reproduce the same set of covariance matrices, necessary and sufficient conditions are stated for the local equivalence of two expanded identified modelsM ₁ andM ₂ when fitting the more restricted modelM ₀. Assuming several regularity conditions, the rank deficiency of the Jacobian matrix, composed of derivatives of the covariance elements with respect to the union of the free parameters ofM ₁ andM ₂ (which characterizes modelM ₁₂), is a necessary and sufficient condition for the local equivalence ofM ₁ andM ₂. This condition is satisfied, in practice, when the analysis dealing with the fitting ofM ₀, predicts that the decreases in the chi-square goodness-of-fit statistic for the fitting ofM ₁ orM ₂, orM ₁₂ are all equal for any set of sample data, except on differences due to rounding errors.This research was supported by the Foundation of Social-Cultural Sciences which is subsidized by the Dutch Scientific Organization (N.W.O.) under project number 500-278-003. The author wishes to thank Anne Boomsma, Ivo Molenaar, Albert Satorra, and Tom Snijders for their stimulating and crucial comments during the research, and the Editor, Paul Bekker, Henk Broer, and anonymous reviewers for their helpful suggestions.