Checking the Assumptions of Rasch's Model for Speed Tests

Two new tests for a model for the response times on pure speed tests by Rasch (1960) are proposed. The model is based on the assumption that the test response times are approximately gamma distributed, with known index parameters and unknown rate parameters. The rate parameters are decomposed in a subject ability parameter and a test difficulty parameter. By treating the ability as a gamma distributed random variable, maximum marginal likelihood (MML) estimators for the test difficulty parameters and the parameters of the ability distribution are easily derived. Also the model tests proposed here pertain to the framework of MML. Two tests or modification indices are proposed. The first one is focused on the assumption of local stochastic independence, the second one on the assumption of the test characteristic functions. The tests are based on Lagrange multiplier statistics, and can therefore be computed using the parameter estimates under the null model. Therefore, model violations for all items and pairs of items can be assessed as a by-product of one single estimation run. Power studies and applications to real data are included as numerical examples.     

Psychometric Modeling of response speed and accuracy with mixed and conditional regression

Human performance in cognitive testing and experimental psychology is expressed in terms of response speed and accuracy. Data analysis is often limited to either speed or accuracy, and/or to crude summary measures like mean response time (RT) or the percentage correct responses. This paper proposes the use of mixed regression for the psychometric modeling of response speed and accuracy in testing and experiments. Mixed logistic regression of response accuracy extends logistic item response theory modeling to multidimensional models with covariates and interactions. Mixed linear regression of response time extends mixed ANOVA to unbalanced designs with covariates and heterogeneity of variance. Related to mixed regression is conditional regression, which requires no normality assumption, but is limited to unidimensional models. Mixed and conditional methods are both applied to an experimental study of mental rotation. Univariate and bivariate analyzes show how within-subject correlation between response and RT can be distinguished from between-subject correlation, and how latent traits can be detected, given careful item design or content analysis. It is concluded that both response and RT must be recorded in cognitive testing, and that mixed regression is a versatile method for analyzing test data.I am grateful to Rogier Donders for putting his data at my disposal.     

The Associations between Mothers’ and Grandmothers’ Depressive Symptoms,Parenting Stress,and Relationship with Children: An Actor–Partner Interdependence Mediation Model

Three-generation households that include parents and grandparents raising children together have become increasingly common in China. This study examined the relations among depressive symptoms, parenting stress, and caregiver–child relationships in the mother–grandmother dyadic context. Participants were mothers and grandmothers from 136 three-generation households. Results from Actor–Partner Interdependence Mediation Modeling indicated that mothers’ depressive symptoms were indirectly related to mother–child conflict/closeness through own parenting stress; grandmothers’ depressive symptoms were indirectly related to grandmother–child conflict through own parenting stress. Mothers’ depressive symptoms were indirectly related to grandmothers’ conflict with children through grandmothers’ parenting stress, and grandmothers’ depressive symptoms were indirectly related to mothers’ conflict/closeness with children through mothers’ parenting stress. The relation between mothers’ parenting stress and mother–child closeness was stronger than the relation between grandmothers’ parenting stress and grandmother–child closeness. Findings highlight the implications of using a family system perspective and the dyadic approach in understanding and improving family functioning in Chinese three-generation households.     

Decision Strategies and the Confidence–Accuracy Relationship in Face Recognition

The decision strategy used to select a choice set from an array of alternative options is known to affect the composition of the final choice set. Specifically, individuals incorporate more answers into their choice set when it is created by eliminating implausible items than when the set is created through the inclusion of plausible options. This difference is accounted for in a decision framework that posits a general reluctance to change the status quo (i.e., actively include or exclude an item). We extended this work to investigate, not only the decisions themselves, but also metacognitive judgments (i.e., confidence in the accuracy of the choice set). In two face recognition experiments, we tested the impact of decision strategy (Experiment 1) and confidence judgment strategy (Experiment 2) on the confidence–accuracy relationship. In Experiment 1, participants completed two blocks of recognition trials, one under inclusion (marking previously seen faces) and one under elimination (marking previously unseen faces) instructions. We observed superior resolution (i.e., discrimination between correct and incorrect) for inclusion trials, but only when they were completed prior to use of the elimination strategy. In Experiment 2, all participants completed face recognition trials under inclusion instructions, but we manipulated the strategy used to assess confidence. Again, we observed a significant impact of strategy on confidence–accuracy resolution. Thus, we observed that both the strategy employed to reach a decision and that employed to assess confidence affected the confidence–accuracy relationship. We discuss theoretical and applied (particularly for eyewitness identification and multiple‐choice testing) implications. Copyright © 2012 John Wiley & Sons, Ltd.     

The impact of empathy and reappraisal on emotional intensity recognition

Empathy represents a fundamental ability that allows for the creation and cultivation of social bonds. As part of the empathic process, individuals use their own emotional state to interpret the content and intensity of other people’s emotions. Therefore, the current study was designed to test two hypotheses: (1) empathy for the pain of another will result in biased emotional intensity judgment; and (2) changing one’s emotion via emotion regulation will modulate these biased judgments. To test these hypotheses, in experiment one we used a modified version of a well-known task that triggers an empathic reaction We found that empathy resulted in biased emotional intensity judgment. To the best of our knowledge, this is the first demonstration of a bias in the recognition of emotional facial expressions as a function of empathy for pain. In experiment two, we replicated these findings in an independent sample, and further found that this biased emotional intensity judgment can be moderated via reappraisal. Taken together, our findings suggest that the novel task used here can be employed to further explore the relation between emotion regulation and empathy.     

On the nature of international sales and sales management research: a social network–analytic perspective

This research uses a combination of text mining, co-word analysis, and social network analysis (SNA) to review 132 international sales and sales management (ISSM) articles published between 1980 and 2017. The study provides a unique view of the past and future of ISSM research and provides three principal contributions. First, from a social network–analytic perspective, it offers a unique examination of the ways ISSM research topics are interconnected, as reflected by keyword network structure. Second, by conducting SNA across two periods (1980–1999 and 2000–2017) and examining the changes in network centrality measures, the study offers initial insights into the evolving nature of the ISSM literature. Third, the study reports keyword network disconnections (i.e., structural holes) to propose a fruitful agenda for future ISSM research. Taken together, this research offers a current perspective of the ISSM research domain's evolving nature.     

Predicting elections from the most important issue: A test of the take‐the‐best heuristic

We used the take‐the‐best heuristic to develop a model to forecast the popular two‐party vote shares in U.S. presidential elections. The model draws upon information about how voters expect the candidates to deal with the most important issue facing the country. We used cross‐validation to calculate a total of 1000 out‐of‐sample forecasts, one for each of the last 100 days of the ten U.S. presidential elections from 1972 to 2008. Ninety‐seven per cent of forecasts correctly predicted the winner of the popular vote. The model forecasts were competitive compared to forecasts from methods that incorporate substantially more information (e.g., econometric models and the Iowa Electronic Markets). The purpose of the model is to provide fast advice on which issues candidates should stress in their campaign. Copyright © 2010 John Wiley & Sons, Ltd.     

Speed of emotional information processing and emotional intelligence

The present study aimed to investigate the relationship between the speed of emotional information processing and emotional intelligence (EI). To evaluate individual differences in the speed of emotional information processing, a recognition memory task consisted of two subtests similar in design but differing in the emotionality of the stimuli. The first subtest required judgment about whether an emotional facial expression in the test face was identical to one of the four emotional expressions of the same individual previously presented. The second subtest required deciding whether the test face with a neutral emotional expression was identical to one of the four neutral faces of different individuals previously presented. Mean response latencies were calculated for “Yes” and “No” responses. All latencies were correlated with other measures of processing speed such as discrimination time and time of figure recognition. However, the emotional expression recognition subtest was hypothesized to require the processing of emotional information in addition to that of facial identity. Latencies in this subtest were longer than those in the face recognition subtest. To obtain a measure of the additional processing that was called for by the emotionality of the stimuli, a subtraction method and regression analysis were employed. In both cases, measures calculated for “No” responses were related to ability EI, as assessed via a self‐report questionnaire. According to structural equation modeling, there was a moderately negative association between latent EI and the latency of “No” responses in the subtest with emotional stimuli. These relationships were not observed for “Yes” responses in the same subtest or for responses in the subtest with neutral face stimuli. Although the differences between “Yes” and “No” responses in their associations with EI require further investigation, the results suggest that, in general, individuals with higher EI are also more efficient in the processing of emotional information.     

Working memory components as predictors of children's mathematical word problem solving

This study determined the working memory (WM) components (executive, phonological loop, and visual–spatial sketchpad) that best predicted mathematical word problem-solving accuracy of elementary school children in Grades 2, 3, and 4 (N = 310). A battery of tests was administered to assess problem-solving accuracy, problem-solving processes, WM, reading, and math calculation. Structural equation modeling analyses indicated that (a) all three WM components significantly predicted problem-solving accuracy, (b) reading skills and calculation proficiency mediated the predictive effects of the central executive system and the phonological loop on solution accuracy, and (c) academic mediators failed to moderate the relationship between the visual–spatial sketchpad and solution accuracy. The results support the notion that all components of WM play a major role in predicting problem-solving accuracy, but basic skills acquired in specific academic domains (reading and math) can compensate for some of the influence of WM on children’s mathematical word problem solving.