Functional measurement approach to self-estimation in multiattribute evaluation

Multiattribute analysis depends on measurement of values and weights. Unless these measures reflect the decision maker's true values and weights, the multiattribute formula may put a less-preferred alternative in first place. To avoid such disordinality requires stringent measurement conditions: First, the values and weights must be on linear (equal interval) or ratio (known zero) scales. Second, these scales must satisfy a condition of common unit across disparate attribute dimensions. Most methods of range adjustment beg both of these measurement questions. Functional measurement theory can solve both problems and so can be useful in multiattribute analysis. Past work has established the operation of a general cognitive algebra as an empirical reality. The averaging model, in particular, makes possible the definition and estimation of weights and values as distinct psychological parameters. It can also solve the problem of common unit. Cognitive algebra thus provides a grounded theoretical foundation on which to develop self-estimation methodology, in which decision makers provide direct estimates of their values and weights. The logic is straightforward. Functional measurement can analyze global judgments to obtain validated psychological scales. These scales may then be used as validational criteria for the self-estimates. Procedures to eliminate biases in the self-estimates can thus be tested and refined in well-learned multiattribute tasks, such as judgments of meals, in which global judgments are trustworthy. Once developed, such self-estimation procedures may be used with some confidence for general multiattribute analysis. A number of studies from 20-odd years of work on the theory of information integration are summarized to show good, although not unmixed promise for self-estimation.     

Individual differences in reverse Hindsight bias: I never thought something like chernobyl would happen. Did I?

Hindsight bias was studied in the context of the accident in the Chernobyl nuclear power plant, which took place on April 26th 1986. An individual difference factor which relates to the motivation to process information, need for cognition, was expected to moderate the occurrence of hindsight bias. Probability estimates of many casualties due to the use of nuclear power in The Netherlands were obtained from 212 individuals two months before the accident in Chernobyl. These estimates were compared with similar estimates made in hindsight by the same individuals five months after the accident. Loglinear Analyses reveal a systematic hindsight bias. However, the direction of the bias was contrary to expectations. In hindsight, individuals gave lower probabilities than they actually did two months before the Chernobyl accident. These results reveal a reverse hindsight bias. As hypothesized, need for cognition moderates hindsight bias: individuals low and medium in need for cognition express a systematic reverse hindsight bias, while individuals high in need for cognition do not. High need for cognition individuals also show higher literal consistency between the two measurements, which supports a memory explanation of the moderating effect of need for cognition.     

Psychological conceptions of randomness

This article presents a critique of the concept of randomness as it occurs in the psychological literature. The first section of our article outlines the significance of a concept of randomness to the process of induction; we need to distinguish random and non-random events in order to perceive lawful regularities and formulate theories concerning events in the world. Next we evaluate the psychological research that has suggested that human concepts of randomness are not normative. We argue that, because the tasks set to experimental subjects are logically problematic, observed biases may be an artifact of the experimental situation and that even if such biases do generalise they may not have pejorative implications for induction in the real world. Thirdly we investigate the statistical methodology utilised in tests for randomness and find it riddled with paradox. In a fourth section we find various branches of scientific endeavour that are stymied by the problems posed by randomness. Finally we briefly mention the social significance of randomness and conclude by arguing that such a fundamental concept merits and requires more serious considerations.     

A structural model for postpartum responses to the somatic and cognitive items on the Beck Depression Inventory

A distinction can be drawn between those items on the Beck Depression Inventory (BDI) that reflect mainly cognitive and emotional symptoms and those that reflect somatic symptoms. Responses to the BDI were obtained from women at 3, 6, 9, and 24 weeks postpartum. The covariances of cognitive and somatic symptom scores across the four time points were closely fit by a structural equations model referred to as the simplex. The modeling indicates that earlier cognitive scores directly predict later somatic scores but that early somatic scores do not directly predict later cognitive scores. Other data confirm the results.Much of this research was supported while the first author was an NIMH Fellow at the University of Iowa (MH15168).     

Work-family spillover of daily positive affect onto performance: The moderating role of domain identity salience

IntroductionA number of linking mechanisms between work and family domains have been studied, but one key mechanism has received little attention: the cross-domain influence of positive affect on performance.ObjectiveThis study examines the work-family spillover of positive affect at work onto performance in the family and, inversely, of positive affect in the family onto performance at work. Drawing upon the work-family enrichment theory (Greenhaus & Powell, 2006), we hypothesized that work and family identity salience moderate the work-to-family and family-to-work relationships between originating domain positive affect and receiving domain performance.MethodA sample of 124 Canadian workers completed a pre-diary survey and daily surveys during 10 consecutive days.ResultsMultilevel analyses showed an effect of daily positive affect in the family on daily performance at work, but no significant effect of daily positive affect at work on daily performance in the family. Furthermore, family identity salience facilitated the work-to-family and family-to-work spillover, whereas work identity salience had no significant moderating effect.ConclusionThe results extend the happy-productive worker thesis to the work-family interface by highlighting that positive affect contextualized in the family is related to performance at work.     

A review on equivalence-based procedures to teach food-portion estimation skills

This review involved a systematic analysis of equivalence-based instruction (EBI) that aimed to improve food-size interventions in diverse populations. Systematic searches identified seven studies published since 2010 that met inclusion criteria. These studies were analyzed according to their participants, design, setting, content taught, training structures, training protocol, testing format, treatment integrity, and outcomes. Results showed EBI procedures for teaching food estimation skills have been mostly implemented with adults. The type of content taught in the identified studies included carbohydrate ranges, portion size with food and non-food items, measuring cups and nutritional content of calories. Majority of included studies used one-to-many training structure and simultaneous protocols for teaching stimulus relations. Five studies completed a generalization probe and three studies reported treatment integrity data. Overall, all participants demonstrated skill acquisition of novel relations between food and portion measurement aides. Recommendations for future research and clinical applications of EBI in teaching food portion estimation are presented.     

An evaluation of the reliability of probability judgments across response modes and over time

Despite the importance of probability assessment methods in behavioral decision theory and decision analysis, little attention has been directed at evaluating their reliability and validity. In fact, no comprehensive study of reliability has been undertaken. Since reliability is a necessary condition for validity, this oversight is significant. The present study was motivated by that oversight. We investigated the reliability of probability measures derived from three response modes: numerical probabilities, pie diagrams, and odds. Unlike previous studies, the experiment was designed to distinguish systematic deviations in probability judgments, such as those due to experience or practice, from random deviations. It was found that subjects assessed probabilities reliably for all three assessment methods regardless of the reliability measures employed. However, a small but statistically significant decrease over time in the magnitudes of assessed probabilities was observed. This effect was linked to a decrease in subjects overconfidence during the course of the experiment.     

The many null distributions of person fit indices

This paper deals with the situation of an investigator who has collected the scores ofn persons to a set ofk dichotomous items, and wants to investigate whether the answers of all respondents are compatible with the one parameter logistic test model of Rasch. Contrary to the standard analysis of the Rasch model, where all persons are kept in the analysis and badly fittingitems may be removed, this paper studies the alternative model in which a small minority ofpersons has an answer strategy not described by the Rasch model. Such persons are called anomalous or aberrant. From the response vectors consisting ofk symbols each equal to 0 or 1, it is desired to classify each respondent as either anomalous or as conforming to the model. As this model is probabilistic, such a classification will possibly involve false positives and false negatives. Both for the Rasch model and for other item response models, the literature contains several proposals for a person fit index, which expresses for each individual the plausibility that his/her behavior follows the model. The present paper argues that such indices can only provide a satisfactory solution to the classification problem if their statistical distribution is known under the null hypothesis that all persons answer according to the model. This distribution, however, turns out to be rather different for different values of the person's latent trait value. This value will be called ability parameter, although our results are equally valid for Rasch scales measuring other attributes.As the true ability parameter is unknown, one can only use its estimate in order to obtain an estimated person fit value and an estimated null hypothesis distribution. The paper describes three specifications for the latter: assuming that the true ability equals its estimate, integrating across the ability distribution assumed for the population, and conditioning on the total score, which is in the Rasch model the sufficient statistic for the ability parameter.Classification rules for aberrance will be worked out for each of the three specifications. Depending on test length, item parameters and desired accuracy, they are based on the exact distribution, its Monte Carlo estimate and a new and promising approximation based on the moments of the person fit statistic. Results for the likelihood person fit statistic are given in detail, the methods could also be applied to other fit statistics. A comparison of the three specifications results in the recommendation to condition on the total score, as this avoids some problems of interpretation that affect the other two specifications.The authors express their gratitude to the reviewers and to many colleagues for comments on an earlier version.     

Inferential procedures for multifaceted coefficients of generalizability

A two-facet measurement model with broad application in the behavioral sciences is identified, and its coefficient of generalizability (CG) is examined. A normalizing transformation is proposed, and an asymptotic variance expression is derived. Three other multifaceted measurement models and CGs are identified, and variance expressions are presented. Next, an empirical investigation of the procedures follows, and it is shown that, in most cases, Type I error control in inferential applications is precise, and that the estimates are relatively efficient compared with the correlation coefficient. Implications for further research and for practice are noted. In an Appendix, four additional models, CGs, and variance expressions are presented.The research reported herein formed part of a doctoral dissertation conducted by Marsha Schroeder (Schroeder, 1986), under the direction of Ralph Hakstian, at the University of British Columbia. We acknowledge with thanks the contributions to this research of Todd Rogers and James Steiger. We are also very indebted to an mous reviewer who provided some important clarifications in connection with two of the models considered. Some support for this research was provided by a grant to Ralph Hakstian from the Natural Sciences and Engineering Research Council of Canada.     

Linear Analogue Self-Assessment and Procrustean Measurement: A Critical Review of Visual Analogue Scaling in Pain Assessment

Visual analogue scales (VASs) are one of the most widely used self-report measures of clinical pain. This article reviews the empirical literature on linear analogue self-assessment (LASA) and critically examines the features that appear to have made it such an attractive measurement option in pain assessment. It is concluded that analogue scaling does not withstand critical scrutiny as a primary measure of either pain intensity or pain affect and that, in most circumstances, the overall clinical utility of VASs is inferior to that of more structured pain indices.