The Impact of Population,Contact, and Spatial Heterogeneity on Epidemic Model Predictions

Our objective was to evaluate the effect that complexity in the form of different levels of spatial, population, and contact heterogeneity has in the predictions of a mechanistic epidemic model. A model that simulates the spatiotemporal spread of infectious diseases between animal populations was developed. Sixteen scenarios of foot‐and‐mouth disease infection in cattle were analyzed, involving combinations of the following factors: multiple production‐types (PT) with heterogeneous contact and population structure versus single PT, random versus actual spatial distribution of population units, high versus low infectivity, and no vaccination versus preemptive vaccination. The epidemic size and duration was larger for scenarios with multiple PT versus single PT. Ignoring the actual unit locations did not affect the epidemic size in scenarios with multiple PT/high infectivity, but resulted in smaller epidemic sizes in scenarios using multiple PT/low infectivity. In conclusion, when modeling fast‐spreading epidemics, knowing the actual locations of population units may not be as relevant as collecting information on population and contact heterogeneity. In contrast, both population and spatial heterogeneity might be important to model slower spreading epidemic diseases. Our findings can be used to inform data collection and modeling efforts to inform health policy and planning.     

Measuring Socio-Demographic Differences in Volunteers with a Value-Based Index: Illustration in a Mega Event

The phenomenon of volunteering can be analysed as a consumer experience through the concept of value as a trade-off between benefits and costs. In event volunteering, both the expected value (pre-experienced) and the perceived value (post-experienced) of volunteering can be assessed. With this purpose, an online quantitative survey is conducted with a sample of 711 volunteers in a religious mega event, with questions related to five dimensions of their experience: efficiency, social value, play, spirituality and time spent. These five scales, properly tested are used for building a multidimensional index of both the expected and perceived value of the volunteer experience. ANOVAs test show significant differences on the index in both moments upon the socio-demographic profiles: negative expectations/experience balance by age, contrasted results by sex, and more experienced volunteers being more critical with the value experienced. Implications for event managers are proposed, in line with the motivation of volunteers.     

What family dimensions are important for health-related quality of life in adolescence?

Adolescence is a relevant life stage in which to study a global well-being measure, health-related quality of life, in order to analyse the impact of important determinants in adolescents' health-related quality of life (e.g., the quality of family relationships). This study aimed to examine the impact of several family dimensions (parental affection, parental promotion of autonomy, family activities, adolescent disclosure, parental solicitation and parental knowledge) on adolescents' health-related quality of life. Additionally, this study investigated whether demographic variables (adolescents' gender and age) influenced health-related quality of life and moderated the relationship between family dimensions and health-related quality of life. The sample was composed of 14,825 adolescents, aged 13–14, 15–16, and 17–18, from the 2006 edition of Spain's Health Behaviour in School-aged Children study. The results showed that parental promotion of autonomy, family activities and especially parental affection were the most important dimensions influencing health-related quality of life. Boys reported higher health-related quality of life than girls, and younger adolescents reported higher health-related quality of life than older adolescents. The discussion explains how the aforementioned family dimensions encourage better health-related quality of life in adolescents.     

促进教学反思实践:校长的策略与启示

教学反思是教师积累教学经验和提高教学质量的必要活动。为了有效地提高教学质量及推行教学改革,校长应将教师教学反思活动有效地融入学校的职业培训项目中。通过系统地介绍教学反思活动的理论背景,包括约翰·杜威的经验学习理论、大卫·库伯的学习周期理论,以及唐纳德·舍恩的专业实践理论,深入地探讨校长在教学反思中起到的作用,以及影响校长促进和支持教学反思进而影响反思活动成效的因素,包括校长的个人素养、专业技能、领导能力以及学校的文化和氛围等。又通过对个人、小组以及学校等不同层面的教学反思,建设性地提出了学校管理层如何采取一系列具体措施来支持和推动教学反思的施行。     

On elliptical multilevel models

Multilevel models have been widely applied to analyze data sets which present some hierarchical structure. In this paper we propose a generalization of the normal multilevel models, named elliptical multilevel models. This proposal suggests the use of distributions in the elliptical class, thus involving all symmetric continuous distributions, including the normal distribution as a particular case. Elliptical distributions may have lighter or heavier tails than the normal ones. In the case of normal error models with the presence of outlying observations, heavy-tailed error models may be applied to accommodate such observations. In particular, we discuss some aspects of the elliptical multilevel models, such as maximum likelihood estimation and residual analysis to assess features related to the fitting and the model assumptions. Finally, two motivating examples analyzed under normal multilevel models are reanalyzed under Student-t and power exponential multilevel models. Comparisons with the normal multilevel model are performed by using residual analysis.     

Diagnostics in multivariate generalized Birnbaum-Saunders regression models

Birnbaum–Saunders (BS) models are receiving considerable attention in the literature. Multivariate regression models are a useful tool of the multivariate analysis, which takes into account the correlation between variables. Diagnostic analysis is an important aspect to be considered in the statistical modeling. In this paper, we formulate multivariate generalized BS regression models and carry out a diagnostic analysis for these models. We consider the Mahalanobis distance as a global influence measure to detect multivariate outliers and use it for evaluating the adequacy of the distributional assumption. We also consider the local influence approach and study how a perturbation may impact on the estimation of model parameters. We implement the obtained results in the R software, which are illustrated with real-world multivariate data to show their potential applications.     

Evaluation of open items using the many-facet Rasch model

The goal of this study is to analyze the quality of ratings assigned to two constructed response questions for evaluating the written ability of essays in Portuguese language from the perspective of the many-facet Rasch (MFR [15 J.M. Linacre, Many-facet Rasch Measurement, 2nd ed., MESA Press, Chicago, 1994. [Google Scholar]]) model. The analyzed data set comes from 350 written tests with two open-item tasks that were developed based on a rating process independently marked by two rater coordinators and a group of 42 raters. The MFR model analysis shows the measurement quality related to the examinees, raters, tasks and items, and classification scale that has been used for the task rating process. The findings indicate significant differences amongst the rater severities and show that the raters cannot be interchanged. The results also suggest that the comparison between the two task difficulties needs further investigation. An additional study has been done on the scale structure of the classification used by each rater for each item. The result suggests that there have been some similarities amongst the tasks and a need of revision for some criteria of the rating process. Overall, the scale of evaluation has shown to be efficient for a classification of the examinees.     

Two new defective distributions based on the Marshall–Olkin extension

The presence of immune elements (generating a fraction of cure) in survival data is common. These cases are usually modeled by the standard mixture model. Here, we use an alternative approach based on defective distributions. Defective distributions are characterized by having density functions that integrate to values less than \(1\), when the domain of their parameters is different from the usual one. We use the Marshall–Olkin class of distributions to generalize two existing defective distributions, therefore generating two new defective distributions. We illustrate the distributions using three real data sets.     

Perception of quality of life in an elderly Angolan sample / Percepción de calidad de vida en una muestra de ancianos angoleños

Increased life expectancy and the ageing of the population have made it particularly important to distinguish between the old (usually 60–79 years, or the ‘young old’) and the oldest old (80 years or more, or the ‘fourth age’). This study explores the effects of age, gender and institutionalization on perceived health and life satisfaction in 1003 elderly people from Luanda, Angola. A multivariate analysis of variance (MANOVA) was estimated to test for these effects. Results provide evidence of lower scores on life satisfaction and perceived health for the oldest old and the institutionalized. However, the higher life satisfaction among the non-institutionalized disappeared when they reach the fourth age. No differences were found by gender, although there was a slight drop in the life satisfaction of women over the age of 80.