Modeling Clustered Data with Very Few Clusters

Small-sample inference with clustered data has received increased attention recently in the methodological literature, with several simulation studies being presented on the small-sample behavior of many methods. However, nearly all previous studies focus on a single class of methods (e.g., only multilevel models, only corrections to sandwich estimators), and the differential performance of various methods that can be implemented to accommodate clustered data with very few clusters is largely unknown, potentially due to the rigid disciplinary preferences. Furthermore, a majority of these studies focus on scenarios with 15 or more clusters and feature unrealistically simple data-generation models with very few predictors. This article, motivated by an applied educational psychology cluster randomized trial, presents a simulation study that simultaneously addresses the extreme small sample and differential performance (estimation bias, Type I error rates, and relative power) of 12 methods to account for clustered data with a model that features a more realistic number of predictors. The motivating data are then modeled with each method, and results are compared. Results show that generalized estimating equations perform poorly; the choice of Bayesian prior distributions affects performance; and fixed effect models perform quite well. Limitations and implications for applications are also discussed.     

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.     

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.     

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.     

基于阶层线性理论的多层级中介效应

本文介绍了三种常见的多层级中介效应模型, 并根据阶层线性理论和依次检验回归系数的方法, 详述了多层级中介效应的检验步骤以及中介效应量的估计方法, 在2-1-1和1-1-1中介效应模型中, 推荐采用对层1自变量按组均值中心化, 同时将组均值置于层2截距方程式的中心化方法, 以实现组间和组内中介效应的有效分离。本文还展望了多层级中介效应模型的拓展方向, 即多层级调节性中介模型和多层级结构方程模型; 以及检验方法的拓展, 即Sobel检验和置信区间检验。     

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.