Measurement invariance,factor analysis and factorial invariance

Several concepts are introduced and defined: measurement invariance, structural bias, weak measurement invariance, strong factorial invariance, and strict factorial invariance. It is shown that factorial invariance has implications for (weak) measurement invariance. Definitions of fairness in employment/admissions testing and salary equity are provided and it is argued that strict factorial invariance is required for fairness/equity to exist. Implications for item and test bias are developed and it is argued that item or test bias probably depends on the existence of latent variables that are irrelevant to the primary goal of test constructers.Presidential address delivered at the Annual Meeting of the Psychometric Society in Berkeley, California, June 18–20, 1993.     

The impact of using forced decision-making strategies on post-decisional confidence

The impact of motivational and cognitive factors on post-decisional confidence (PDC) level was tested in two experiments. In the first experiment, subjects were first identified as having an intuitive preference toward using either a compensatory or a noncompensatory decision strategy and later on were forced to use either a compatible or a non-compatible strategy. PDC level decreased after using a noncompensatory strategy, and the decrease was higher when it was a noncompatible strategy. In a second experiment, subjects received feedback about their preferred strategy but were not later forced to use any specific strategy. Most subjects continued to utilize their preferred strategy and PDC level was not changed. Overall, intuitive PDC was not found to be sensitive to differences between compensatory and noncompensatory strategies. The result suggested that PDC is a function of an internal cost-benefit analysis which includes both cognitive and motivational factors.     

Selecting entrepreneurial employees using a person-group fit perspective

As jobs become unstructured and collective endeavor oriented, it is increasingly being realized that work groups must become more autonomous and entrepreneurial. The selection literature is however silent on the predictive mechanisms that may be leveraged to select group members with the desired competencies. The person-group fit perspective enables us to hypothesize and demonstrate that selection instruments geared toward gauging an individual's fit within a group are likely to manifest entrepreneurial competencies and behaviors in the individual. Further, the nature of the job, in terms of the structuredness of work (task formalization) and the repetitiveness of work activities (task routinization), has a moderating impact on the relationship between overall entrepreneurial competence and selection practices. The study has implications for incorporating the principles of person-group fit into the design of job profiles.     

: Applicants' experiences with discrimination explain their reactions to algorithms in personnel selection

Algorithms might prevent prejudices and increase objectivity in personnel selection decisions, but they have also been accused of being biased. We question whether algorithm-based decision-making or providing justifying information about the decision-maker (here: to prevent biases and prejudices and to make more objective decisions) helps organizations to attract a diverse workforce. In two experimental studies in which participants go through a digital interview, we find support for the overall negative effects of algorithms on fairness perceptions and organizational attractiveness. However, applicants with discrimination experiences tend to view algorithm-based decisions more positively than applicants without such experiences. We do not find evidence that providing justifying information affects applicants—regardless of whether they have experienced discrimination or not.     

Evaluating the desirability of meals: an illustrative multiattribute decision analysis procedure to assess portfolios with interdependent items

This paper presents an exploratory study designed to address complex scaling problems in applying value/utility theory to measuring preferences over alternative combinations (or portfolios) of multiattributed items. This application considers meals served to nursing home residents as portfolios of food items and seeks to maximize meal appeal. We consider food interrelation and link single food measurements to overall meal measurements in the process of constructing meal desirability scales. We test the resulting scales to capture one expert's professional judgments and discuss issues raised in this specific application in the context of general portfolio evaluation problems. © 1998 John Wiley & Sons, Ltd.     

Unemployment and Health: Selection Effects

A large number of studies have shown that the unemployed are less healthy, both physically and psychologically, than the employed. The explanation may be that unemployment has negative health effects. An alternative, or additional, explanation is that healthy persons are less likely to become unemployed or more likely to find new employment if they become unemployed. Such effects of health on employment status are generally referred to as selection effects. The present paper analyses to what extent such selection effects are present in the Norwegian labour market. Panel data with observations made in 1989 and 1993 are used. The analyses show that people with psychological problems are more likely to be laid off, and there is also some evidence that psychological or physical health problems may reduce the chances of finding a new job if one has become unemployed. It is of particular interest that these selection effects can be documented for a country like Norway, which has strong legislation supporting worker rights and a quite high degree of unionization.     

Stepwise variable selection in factor analysis

It is very important to choose appropriate variables to be analyzed in multivariate analysis when there are many observed variables such as those in a questionnaire. What is actually done in scale construction with factor analysis is nothing but variable selection.In this paper, we take several goodness-of-fit statistics as measures of variable selection and develop backward elimination and forward selection procedures in exploratory factor analysis. Once factor analysis is done for a certain numberp of observed variables (thep-variable model is labeled the current model), simple formulas for predicted fit measures such as chi-square, GFI, CFI, IFI and RMSEA, developed in the field of the structural equation modeling, are provided for all models obtained by adding an external variable (so that the number of variables isp + 1) and for those by deleting an internal variable (so that the number isp – 1), provided that the number of factors is held constant.A programSEFA (Stepwise variable selection in Exploratory Factor Analysis) is developed to actually obtain a list of the fit measures for all such models. The list is very useful in determining which variable should be dropped from the current model to improve the fit of the current model. It is also useful in finding a suitable variable that may be added to the current model. A model with more appropriate variables makes more stable inference in general.The criteria traditionally often used for variable selection is magnitude of communalities. This criteria gives a different choice of variables and does not improve fit of the model in most cases.The URL of the programSEFA is http://koko15.hus.osaka-u.ac.jp/~harada/factor/stepwise/.     

平面几何解题过程中加工水平对迁移的影响

通过实验研究,平面几何靶题难度以及解题者对靶题与源题之间存在着共性关系的加工水平对解题迁移的影响得到了验证。结果表明,解题者对具有内在联系的先后问题之间共性关系的加工水平是影响解题迁移的因素之一;靶题的难度太大或太小,将导致解题者对先后问题之间共性关系的加工作用失败而出现地板效应和天花板效应,且靶题难度与加工水平在影响解题迁移时有交互作用。     

New approaches to the ‘crucial’ test of the causation and selection hypotheses in a Northern Irish sample

This paper examines the relationship between minority/majority status and psychological adjustment, as measured by the GHQ‐12. Rather than using religious labels in Northern Ireland to define minority/majority status, the authors hypothesized that such status is more contingent upon the local area context. Using a purer operationalization of minority/majority status, the authors found no evidence of an ‘ethnic density effect’. Implications for the questionable validity of the ‘crucial test’ of the selection and causation hypotheses are discussed. Copyright © 2002 John Wiley & Sons, Ltd.     

基于基尼指数的双目标CD-CAT选题策略

双目标CD-CAT的测验结果既可用于形成性评估也可用于终结性评估。基尼指数可度量随机变量的不确定性程度, 值越小则随机变量的不确定程度越低。本文用基尼指数度量被试知识状态类别以及能力估计置信区间后验概率的变化, 提出基于基尼指数的选题策略。Monte Carlo实验表明与已有的选题策略相比, 新策略的知识状态分类精度和能力估计精度都较高, 同时能有效兼顾题库利用均匀性, 并能快速实时响应, 且受认知诊断模型和被试知识状态分布的影响较小, 可用于实际测验中含多种认知诊断模型的混合题库。