Modelling individual difference in visual categorization

Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modelling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization.     

Temporal dynamics of need satisfaction and need frustration. Two sides of the same coin?

We study the dynamics of need satisfaction and need frustration by examining how need satisfaction and need frustration change over time and how these changes relate to changes in motivation. To investigate this, volunteers were assessed daily during a delineated activity, resulting in a total sample of 77 volunteers and 467 completed daily diaries. Bayesian confirmatory factor analysis on the within-person level confirmed a bifactor solution: autonomy, competence, and relatedness were distinguished by three specific factors, but the majority of variance was explained by two strongly correlated (need satisfaction and need frustration) factors. The strong correlation between need satisfaction and need frustration further translated in the development of their relationship over time. That is, Bayesian latent growth curve modelling revealed a simultaneous, yet opposite, growth curve. Contrary to our expectations, neither of them could be related to behavioural internalization or externalization. These results imply that, at the within-person level, momentary need satisfaction and frustration are difficult to distinguish, and affecting one may automatically affect the other. Also, the relationships within the self-determination framework, such as the proposed link between need satisfaction and behavioural internalization may be better reframed with attention to the time-frame in which they occur.     

Promoting fan engagement: An exploration of the fundamental motives for sport consumption amongst premier league football spectators

The aim of this study was to examine whether fan engagement could be predicted by the motivational dimensions of sport consumption. A sample of 806 football sport fans (African = 85%, male = 67.4%, part of an organised supporters club = 57.6%) were participants. They completed the Fan Engagement Scale (FES), the Motivation Scale for Sport Consumption (MSSC) and a biographical questionnaire. Structural equation modelling was applied to evaluate the postulated regressive paths between the motivational dimensions for sports consumption and fan engagement. The motivational dimensions for sport consumption were clustered into personal and game-related factors. Both these clusters of factors were predictive of fan engagement. Customer engagement (CE) theory appears to explain the findings.     

Counterfactual thinking as an issue between language and pretend play / El pensamiento contrafactual como un problema entre el lenguaje y el juego de simulación

Discussions on counterfactual thinking (CT) have been focused on whether it is a language skill or it emerges spontaneously before language acquisition. This paper surveys the most compelling arguments regarding these frameworks: (1) the approach ‘CT as a language skill’; (2) those who claim that pretending shows that children have CT; (3) those who consider pretend play is a rehearsal for cognitive dispositions. I shall point out that the three approaches on CT are incomplete: (1) neglects pretend play (which prelinguistic children perform) as an instantiation of the CT; (2) puts too much emphasis on the linguistic dimension of pretense; (3) is highly demanding on the cognitive architecture that we ought to have by nature — the so-called children as scientists.     

The stress of food allergy issues in daily life

Objective: Food allergies are a growing health concern, but their implications for daily psychological functioning are unknown. This micro-longitudinal study investigated the daily frequency of food allergy issues and how this related to experiences of stress, mood and physical energy.

Design: One hundred and eight adults with physician-diagnosed food allergies completed an initial Internet survey followed by a 2-week Internet daily diary survey.

Main outcome measures: The initial survey collected socio-demographic and food allergy information. The daily survey collected information about the participants’ experiences of stress, mood, physical energy and food allergy issues during that day.

Results: Commonly experienced allergy issues included negative physical symptoms, higher food prices, anxiety about safety of food, trouble maintaining a healthy diet and anxiety/stress at social occasions. Furthermore, multilevel modelling analyses showed that stress and negative mood were significantly higher on days with more allergy issues. Older adults experienced lower positive mood and physical energy on days with more issues.

Conclusion: This is the first study to incorporate near to real-time tracking to examine the frequency of food allergy issues and the implications for daily psychological functioning. Targeting the issues we identified could reduce stress in patients with food allergies and improve their overall quality of life.     

Leaping to Conclusions: Why Premise Relevance Affects Argument Strength

Everyday reasoning requires more evidence than raw data alone can provide. We explore the idea that people can go beyond this data by reasoning about how the data was sampled. This idea is investigated through an examination of premise non‐monotonicity, in which adding premises to a category‐based argument weakens rather than strengthens it. Relevance theories explain this phenomenon in terms of people's sensitivity to the relationships among premise items. We show that a Bayesian model of category‐based induction taking premise sampling assumptions and category similarity into account complements such theories and yields two important predictions: First, that sensitivity to premise relationships can be violated by inducing a weak sampling assumption; and second, that premise monotonicity should be restored as a result. We test these predictions with an experiment that manipulates people's assumptions in this regard, showing that people draw qualitatively different conclusions in each case.     

A statistical model of cleavage fracture in structural steels with power-law distribution of microcrack size

Based on the well-accepted physical understanding that cleavage fracture of structural steels is preceded by plastic deformation, a critical flaw in the Beremin model and its modifications is proposed, and a new statistical model with the power-law distribution of microcracks is obtained to describe the cumulative probability of cleavage fracture. A set of cleavage fracture toughness data of a nuclear pressure vessel steel is used to highlight the difference between the new model and the Beremin model.     

Associations between parental gendered attitudes and behaviours and children’s gender development across middle childhood

The present study used a longitudinal, multi-informant approach to examine which specific elements of parents’ gendered attitudes and behaviours were predictive of multiple dimensions of children’s gender development. One hundred and six families with two children (older sibling M = 7.45 years and younger sibling M = 5.19 years at Time 1) were assessed at two time points four to five years apart. At Time 1, parents reported on division of household labour, their own gender-role attitudes (GRAs), and children’s gendered preferences. At Time 2, children reported on their gendered preferences, GRAs and gendered personality traits. Results from multilevel modelling showed that fathers’ egalitarian GRA and egalitarian division of household tasks were predictive of egalitarian child GRA and outcomes, but child sex did not moderate these relationships. As some gender measures were more strongly correlated than others, these findings highlight the importance of examining multiple dimensions of both children’s and parents’ gendered attitudes and behaviours.     

Preference Structure Modelling for Multi-objective Decision Making: A Goal–Programming Approach

We propose a new approach for modelling preference structures in multi-objective decision-making (MODM) problems. The basic idea of the approach is to first develop PROMETHEE-influenced objective functions and then to use these to reformulate the problem as a distance-based goal–programming (GP) model. Three basic functional forms are proposed and explicit expressions are developed for them. Among other things, the expressions allow for the straightforward development of an interactive framework while keeping the information requirements from the decision maker (DM) at a minimum. An ‘automatic’ piecewise linear approximation scheme is proposed for solving the GP model. © 1997 by John Wiley & Sons, Ltd. J. Multi-Crit. Decis. Anal. 6 : 150–154 (1997) No. of Figures: 0. No. of Tables: 0. No. of References: 12.     

Optimal designs for the generalized partial credit model

Analysing ordinal data is becoming increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and has found application in many large-scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons’ abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We find that local optimality may be achieved by assigning non-zero probability only to the first and last categories independently of a person's ability. That is, when using such a design, the GPCM reduces to the dichotomous two-parameter logistic (2PL) model. Since locally optimal designs require the true ability to be known, we consider alternative Bayesian design criteria using weight distributions over the ability parameter space. For symmetric weight distributions, we derive necessary conditions for the optimal one-point design of two response categories to be Bayes optimal. Furthermore, we discuss examples of common symmetric weight distributions and investigate under what circumstances the necessary conditions are also sufficient. Since the 2PL model is a special case of the GPCM, all of these results hold for the 2PL model as well.