情绪测量方法的新进展

当代情绪理论认为情绪反应包括生理唤醒、行为反应、面部行为或姿势、以及主观体验等成分。随着时代进步和科技发展,对其的测量也日趋细化,主要包括自我报告法、自主神经系统测量、惊跳反应测量、脑测量及行为测量等方法。大量情绪研究的证据表明,情绪反应的测量多是通过情绪维度（如效价、唤醒度）和基本情绪状态（如,悲伤、恐惧、愤怒）两种方式组织起来的,不同的情绪测量方法对不同的组织方式敏感。未来的情绪测量的标准是多元的,其测量方法的确立是以特定的情绪问题为基础的。     

A multi-criterion experimental comparison of three multi-attribute weight measurement methods

The research compared three major multi-attribute weight measurement methods using multiple criteria: theoretical validity, predictive performance, and perceived performance. Major findings include (1) all three methods are theoretically valid using the EAM (Equal Weight Averaging Model) as the standard of comparison, (2) EAM outperforms SMART (Simple Multi-Attribute Rating Technique) and SMART outperforms AHP (Analytical Hierarchy Process) in terms of predictive performance, (3) in terms of perceived performance, EAM is considered more difficult and less preferred than AHP, but has equal trustworthiness. The research has demonstrated how self-estimation methods for multi-attribute analysis can be verified and improved theoretically and empirically by using weights and values from the EAM model as a theoretical validity standard. © 1998 John Wiley & Sons, Ltd.     

Using a supervised machine learning algorithm for detecting faking good in a personality self‐report

We developed a supervised machine learning classifier to identify faking good by analyzing item response patterns of a Big Five personality self‐report. We used a between‐subject design, dividing participants (N = 548) into two groups and manipulated their faking behavior via instructions given prior to administering the self‐report. We implemented a simple classifier based on the Lie scale's cutoff score and several machine learning models fitted either to the personality scale scores or to the items response patterns. Results shown that the best machine learning classifier—based on the XGBoost algorithm and fitted to the item responses—was better at detecting faked profiles than the Lie scale classifier.     

Examining the cross‐cultural validity of the positive affect and negative affect schedule between an Asian (Singaporean) sample and a Western (American) sample

The positive affect and negative affect schedule (PANAS) is a popular measure of positive (PA) and negative affectivity (NA). Developed and validated in Western contexts, the 20‐item scale has been frequently administered on respondents from Asian countries with the assumption of cross‐cultural measurement invariance. We examine this assumption via a rigorous multigroup confirmatory factor analysis, which allows us to assess between‐group differences in both strength of scale item‐to‐latent factor relationship (metric invariance test) and mean of each scale item (scalar invariance test), on a large sample of 1,065 respondents recruited from Singapore (Asian sample) and the United States (Western sample). We found that two items assessing PA (“excited” and “proud”) and three items assessing NA (“guilty,” “hostile,” and “ashamed”) exhibited metric noninvariance whereas 11 of the remaining metric invariant items exhibited scalar noninvariance, suggesting that the PA and NA constructs differ from what the PANAS is expected to measure for Asian respondents. Our findings serve as a cautionary note to researchers who intend to administer the PANAS in future studies as well as to researchers interpreting the results of past studies involving respondents from Asian countries.     

Does God Cheat at Dice? Divine Action and Quantum Possibilities

The recent debates concerning divine action in the context of quantum mechanics are examined with particular reference to the work of William Pollard, Robert J. Russell, Thomas Tracy, Nancey Murphy, and Keith Ward. The concept of a quantum mechanical "event" is elucidated and shown to be at the center of this debate. An attempt is made to clarify the claims made by the protagonists of quantum mechanical divine action by considering the measurement process of quantum mechanics in detail. Four possibilities for divine influence on quantum mechanics are identified and the theological and scientific implications of each discussed. The conclusion reached is that quantum mechanics is not easily reconciled with the doctrine of divine action.     

Measuring Adherence to Medical Treatments in Childhood Chronic Illness: Considering Multiple Methods and Sources of Information

Adherence to medical treatment is a significant problem for children and adolescents with chronic conditions, such as asthma, diabetes, and cystic fibrosis. The consequences of nonadherence can be serious, contributing to increased symptoms, unnecessary hospitalizations, and declines in physical functioning. The quality of data obtained from clinical trials can also be affected by poor adherence, leading to erroneous conclusions concerning the efficacy of drug treatments and the dosages that are needed to achieve those effects. Adherence problems in both clinical research and practice also lead to substantially higher health care costs. In order to further our understanding of the barriers that lead to poor adherence and identify strategies that are effective in addressing them, we need to develop reliable and valid measures of adherence behaviors. Using cystic fibrosis as a model of a serious, chronic disease that requires a difficult and time-consuming medical regimen, three different types of adherence measures are considered: self-report questionnaires, daily diary reports, and electronic monitors. The specific advantages and disadvantages of each type of measurement are reviewed, and specific recommendations are made for future research.     

多维效标测量的构成

通过为某机床企业销售员制定一套自我绩效评定迫选量表,收集判断性效标测量和非判断性效标测量,研究判断性效标测量和非判断性效标测量与自我绩效评定迫选量表中各工作行为的关系,验证了两个假设：(1)任一效标测量不可能与所有有效工作行为显著相关;(2)在效标测量中,既应采用判断性效标测量,也应采用非判断性效标测量,二者互相补充,不可替代。     

A comparison of latent trait and latent class analyses of Likert-type data

This paper brings together and compares two developments in the analysis of Likert attitude scales. The first is the generalization of latent class models to ordered response categories. The second is the introduction of latent trait models with multiplicative parameter structures for the analysis of rating scales. Key similarities and differences between these two methods are described and illustrated by applying a latent trait model and a latent class model to the analysis of a set of life satisfaction data. The way in which the latent trait model defines a unit of measurement, takes into account the order of the response categories, and scales the latent classes, is discussed. While the latent class model provides better fit to these data, this is achieved at the cost of a logically inconsistent assignment of individuals to latent classes.The author wishes to thank Clifford C. Clogg, Otis Dudley Duncan and Benjamin D. Wright for their helpful comments on an earlier version of this paper.     

Conformity of two sociometric relations

The problem of comparing two sociometric relations or measurements (A andB) recorded in distinct sociomatrices was originally discussed by Katz and Powell in the early 1950's and Hubert and Baker in the late 1970's. The problem is considered again using a probabilistic model designed specifically for discrete-valued network measurements. The model allows for the presence of various structural tendencies, such as reciprocity and differential popularity. A parameter that isolates the tendency for actors to choose other actors on both relations simultaneously is introduced, and estimated conditional on the presence of other parameters that reflect additional important network properties. The parameter is presented as a symmetric index but is also generalized to the predictive (A onB orB onA) situation. This approach to the problem is illustrated with the same data used by the earlier solutions, and the unique nature of the two relations in the data set (A = received choices,B = perceived choices), as it affects the modeling, is discussed. Significance tests for the parameter and related parameters are described, as well as an extension to more than two relations.Research support provided by National Science Grant #SES84-08626 to the University of Illinois at Urbana-Champaign. I am grateful to Dawn Iacobucci and Sheila Weaver for assistance with the research reported here, and to Carolyn Anderson, James Green, David Holtgrave, and four anonymous referees for comments on the paper.