A l'occasion du renouvellement de l'annee

Sans résumé     

Links Among Cognitive Empathy,Theory of Mind,and Affective Perspective Taking by Young Children

The authors investigated the development of the affective, cognitive, and behavioral components of empathy in preschoolers, specifically examining how cognitive empathy is linked to theory of mind and affective perspective taking. Participants were 158 children aged 4–6 years. They listened to narratives and then answered questions about the protagonists' emotions. The affective component was probed with the question, “How do you feel seeing the little girl/boy?”; the cognitive component with the question, “Why do you feel [emotion shared with the character]?”; and the behavioral one with the question, “What would you do if you were next to the little boy/girl [experiencing an emotional scenario]?” Results revealed a developmental sequence in the self-focused attribution of cognitive empathy, and a trend toward a developmental sequence for behavioral empathy, which underwent a slight linear increase between 4 and 6 years old. Affective empathy remained stable. More interestingly, they showed that cognitive empathy is linked to both theory of mind and affective perspective taking.     

A two‐part mixed effects model for cigarette purchase task data

The Cigarette Purchase Task is a behavioral economic assessment tool designed to measure the relative reinforcing efficacy of cigarette smoking across different prices. An exponential demand equation has become a standard model for analyzing purchase task data, but its utility is compromised by its inability to accommodate values of zero consumption. We propose a two‐part mixed effects model that keeps the same exponential demand equation for modeling nonzero consumption values, while providing a logistic regression for the binary outcome of zero versus nonzero consumption. Therefore, the proposed model can accommodate zero consumption values and retain the features of the exponential demand equation at the same time. As a byproduct, the logistic regression component of the proposed model provides a new demand index, the “derived breakpoint”, for the price above which a subject is more likely to be abstinent than to be smoking. We apply the proposed model to data collected at baseline from college students (N = 1,217) enrolled in a randomized clinical trial utilizing financial incentives to motivate tobacco cessation. Monte Carlo simulations showed that the proposed model provides better fits than an existing model. We note that the proposed methodology is applicable to other purchase task data, for example, drugs of abuse.     

Correction for Range Restriction in Meta‐Analysis Revisited: Improvements and Implications for Organizational Research

In this study, we present a more accurate method for correcting for range restriction (Case V) that expands upon Bryant and Gokhale's (1972) method. We further present detailed steps to incorporate the Case V method into Schmidt and Hunter's (2015) psychometric meta‐analysis methods (both individual correction and artifact distribution approaches). We then evaluate the accuracy of the Case V method vis‐à‐vis existing methods. Monte‐Carlo simulation results indicate that the Case V method provides very accurate estimates for the mean true score correlation and reasonably accurate estimates for the true standard deviation. More important, Case V almost always provides more accurate results than alternative methods (particularly, Case IV). To illustrate how the Case V method works with real data, we conduct a reanalysis of Judge, Heller, and Mount's (2002) meta‐analysis examining the relationships between the Big 5 personality traits and job satisfaction. Results indicate that the true score correlations between the Big 5 traits and job satisfaction have been underestimated, whereas their true standard deviations have been overestimated. Implications for range restriction corrections in organizational research are discussed.     

Predictive model for early math skills based on structural equations

Early math skills are determined by higher cognitive processes that are particularly important for acquiring and developing skills during a child's early education. Such processes could be a critical target for identifying students at risk for math learning difficulties. Few studies have considered the use of a structural equation method to rationalize these relations. Participating in this study were 207 preschool students ages 59 to 72 months, 108 boys and 99 girls. Performance with respect to early math skills, early literacy, general intelligence, working memory, and short‐term memory was assessed. A structural equation model explaining 64.3% of the variance in early math skills was applied. Early literacy exhibited the highest statistical significance (β = 0.443, p < 0.05), followed by intelligence (β = 0.286, p < 0.05), working memory (β = 0.220, p < 0.05), and short‐term memory (β = 0.213, p < 0.05). Correlations between the independent variables were also significant (p < 0.05). According to the results, cognitive variables should be included in remedial intervention programs.