Validating a selection test,a predictive probability approach

The problem of inferring the validity of a selection test (x) as a predictor of some criterion (y) when completexy data are not available is investigated. The basic approach is to construct the predictive probability distribution of the unobservedy scores and then derive interval estimates of the least squares regression weights, the difference in averagey scores for selected and unselected cases, and the residual variance in predictingy fromx. Further, an approximation to the predictive distribution of the squared correlation betweenx andy in a future group is derived.     

An optimal property of least squares weights in prediction models

In predicting scores fromp > 1 observed scores in a sample of sizeñ, the optimal strategy (minimum expected loss), under certain assumptions, is shown to be based upon the least squares regression weights computed from a previous sample. Letting represent the correlation between and the predicted values , and letting represent the correlation between and a different set of predicted values , where w is any weighting system which is not a function of , it is shown that the probability of being less than cannot exceed .50. The relationship of this result to previous research and practical implications are discussed.     

A similarity-based smoothing approach to nondimensional item analysis

The probability that an examinee chooses a particular option within an item is estimated by averaging over the responses to that item of examinees with similar response patterns for the whole test. The approach does not presume any latent variable structure or any dimensionality. But simulated and actual data analyses are presented to show that when the responses are determined by a latent ability variable, this similarity-based smoothing procedure can reveal the dimensionality of ability very satisfactorily.The author wishes to acknowledge the support of the Natural Sciences and Engineering Research Council of Canada through grant A320, and to thank Educational Testing Service for making the data on the Advanced Placement Chemistry Exam available.     

区分度和难度分布在测验效度上的效应比较的模拟试验研究

运用计算机模拟试验方法,研究了４种不同的区分度分布和４种不同的难度分布在测验效度上的效应变化规律。结果表明：（１）在难度分布一定的条件下,测验效度随测验中较高区分度的项目数的递增而单调地提高;（２）在区分度分布一定的条件下,测验中的项目难度分布与考生的能力分布相一致时测验放度较高;（３）区分度分布对效度的影响比难度分布的影响更直接。     

Fitting multivariage normal finite mixtures subject to structural equation modeling

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the differences between the components in the mixture. Within the general model, individual parameters can be subjected to equality, nonlinear and simple bounds constraints. Confidence intervals are based on the inverse of the Hessian and on the likelihood profile. Several illustrations are given and results of a simulation study concerning the confidence intervals are reported.     

Estimation of interhemispheric dynamics from simple unimanual reaction time to extrafoveal stimuli

This essay reviews research on interhemispheric transfer time derived from simple unimanual reaction time to hemitachistoscopically presented visual stimuli. Part 1 reviews major theoretical themes including (a) the significance of the eccentricity effect on interhemispheric transfer time in the context of proposed underlying neurohistological constraints; (b) the significance of gender differences in interhemispheric transfer time and findings in dyslexics and left-handers in the context of a fetal brain testosterone model; and (c) the significance of complexity effects on interhemispheric transfer time in a context of dynamic vs. hard-wired concepts of the underlying interhemispheric communication systems. Part 2 consists of a meta-analysis of 49 published behavioral experiments, in view of drawing a portrait of the best set of experimental conditions apt to produce salient, reliable, and statistically significant measures of interhemispheric transfer time, namely (a) index rather than thumb response, (b) low rather than high target luminance, (c) short rather than prolonged target display, and (d) very eccentric rather than near-foveal stimulus location. Part 3 proposes a theoretical model of interhemispheric transfer time, postulating the measurable existence of fast and slow interhemispheric channels. The proposed mechanism's evolutionary adaptive value, the neurophysiological evidence in its support, and favorable functional evidence from studies of callosotomized patients are then presented followed by proposals for critical experimental tests of the model.     

Points of view analysis revisited: Fitting multidimensional structures to optimal distance components with cluster restrictions on the variables

Points of view analysis (PVA), proposed by Tucker and Messick in 1963, was one of the first methods to deal explicitly with individual differences in multidimensional scaling, but at some point was apparently superceded by the weighted Euclidean model, well-known as the Carroll and Chang INDSCAL model. This paper argues that the idea behind points of view analysis deserves new attention, especially as a technique to analyze group differences. A procedure is proposed that can be viewed as a streamlined, integrated version of the Tucker and Messick Process, which consisted of a number of separate steps. At the same time, our procedure can be regarded as a particularly constrained weighted Euclidean model. While fitting the model, two types of nonlinear data transformations are feasible, either for given dissimilarities, or for variables from which the dissimilarities are derived. Various applications are discussed, where the two types of transformation can be mixed in the same analysis; a quadratic assignment framework is used to evaluate the results.The research of the first author was supported by the Royal Netherlands Academy of Arts and Sciences (KNAW); the research of the second author by the Netherlands Organization for Scientific Research (NWO Grant 560-267-029). An earlier version of this paper was presented at the European Meeting of the Psychometric Society, Leuven, 1989. We wish to thank Willem J. Heiser for his stimulating comments to earlier versions of this paper, and we are grateful to the Editor and anonymous referees for their helpful suggestions.     

An INAR(1) negative multinomial regression model for longitudinal count data

This paper discusses a regression model for the analysis of longitudinal count data observed in a panel study. An integer-valued first-order autoregressive [INAR(1)] Poisson process is adapted to represent time-dependent correlations among the counts. By combining the INAR(1)-representation with a random effects approach, a new negative multinomial distribution is derived that includes the bivariate negative binomial distribution proposed by Edwards and Gurland (1961) and Subrahmaniam (1966) as a special case. A detailed analysis of the relationship between personality factors and daily emotion experiences illustrates the approach.This research was partially supported by NSF grant SBR-9409531. The author is grateful to Ulrich Schimmack and Ed Diener for providing the data set used in the application section and for helpful comments on this research.     

Global Progress II: Evolutionary Mechanisms and their Side-effects

This paper attempts to update the 18th century concept of progress by an evolutionary theoretical framework, while replying to some of the contemporary critiques. Progress, understood as increase in fitness (or its proxy, quality of life) necessarily accompanies evolution by natural selection. In socio-cultural evolution, this mechanism is reinforced by growth of knowledge and virtuous cycles, but can be accompanied by negative side-effects such as overshooting and parasitism. The most pressing of the contemporary side-effects, such as pollution and the increased pace of life, are discussed, but it is concluded that they can be tackled without really endangering global progress. The anxiety that they engender is unfortunately amplified by a bad news bias in the media, leading to an inappropriately pessimistic view of the situation by the public.     

组织决策的影响力分布

从行动理论的角度分析了组织决策的特征,提出了组织决策的阶段层次理论,并认为：１．决策过程的本质在于形成决策问题的目标手段层次结构;２．决策的层次结构具有阶段性特征,即它是随决策阶段的进展而逐步分化、完善的;３．组织在其结构上也是一个由分化得来的层次结构。因此,在组织决策过程中,应该根据决策的阶段特征,充分发挥相应组织层次的作用。关于各决策阶段组织影响力分布的调查得到了与理论模型一致的结果,有决策影响力的群体随决策阶段的展开而分化：在决策阶段一直存在两个决策影响力群体,一个是高层管理,另一个是中层管理、基层管理和工人;而在决策阶段二和三,中层管理逐步分化出来,成为第三个独立的影响力群体;在决策阶段四,基层管理代表工人参与决策的作用得到了充分的显示。此外,本研究结果还指出了高层管理在后三个阶段中对组织决策影响力分布的决定作用