Some Results Based on a Version of the Generalized Dynamic Entropies

We propose new dynamic measures of uncertainty based on the notion of generalized dynamic entropy introduced in Di Crescenzo and Longobardi (2006). These can uniquely determine distribution functions in continuous and discrete cases, and the characterizations of some well-known distributions are provided. We also define some orderings and aging notions based on the generalized dynamic measures, and prove some of their properties, obtaining as corollaries results that have recently appeared in the literature.     

Culture Change in Aged-Care Facilities: A Café's Contribution to Transforming the Physical and Social Environment

Objective: To discuss the potential of a café on the premises of an aged-care facility as a vehicle for culture change. Method: Secondary analysis of primary qualitative data that explored the value of a café in an aged-care facility, compared with culture-change principles established from a literature review. Results: Secondary analysis established congruence between culture-change principles and the themes established in the primary qualitative data. A café, in one aged-care facility, has facilitated the following dimensions of culture change for residents: individualized care, facilitation of meaningful relationships, opportunities for participation in life roles, and creation of a sense of belonging. Conclusion: Culture change can be achieved through environmental innovations, such as a café, where food and dining maximize social opportunities and create a homelike environment that facilitates continuation of residents' identity.     

Beyond mere information transfer: The importance of a relational approach to market-related internal communication

Despite the significance of relationship management in any information provision or exchange, public relations scholarship has typically focused on examining the underlying internal communication processes from a transactional perspective. These processes are frequently associated with organizational information dissemination, overlooking other critical contents to make strategic decisions. This study draws market information processing into the debate about internal communication, providing a greater understanding of how a relational approach can improve market intelligence dissemination. Results show that an effective management of market knowledge requires the use of such an approach, which in turn, cultivates the shared interpretation of market information and innovation performance. The findings stimulate fresh discussion about the nature and development of internal communication knowledge and practice.     

Generalized information matrix tests for copulas

We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Tail Behavior and Limit Distribution of Maximum of Logarithmic General Error Distribution

Logarithmic general error distribution, an extension of the log-normal distribution, is proposed. Some interesting properties of the log GED are derived. These properties are applied to establish the asymptotic behavior of the ratio of probability densities and the ratio of the tails of the logarithmic general error and log-normal distributions, and to derive the asymptotic distribution of the partial maximum of an independent and identically distributed sequence obeying the log GED.     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Generalizability of an adult-validated model for predicting increased physical activity in after-school program children: Effects of treatment formats on fitness indicators

Inappropriately high weight in children is a persistent problem in the United States, and physical activity is often reduced in schools due to academic demands. Effective after-school programs could positively impact both physical activity and overweight/obesity, however previous reviews and meta-analyses have indicated minimal effects. Both 4- and 3-day/week versions of a social cognitive theory-driven physical activity/nutrition after-school program were evaluated against unstructured care to assess effects in children (overall M_age = 10.00 years, SD = .80). For changes over 9 months in body mass index (BMI), effects sizes (Cohen’s d) were .68, .40, and .07 in the 4-day (n = 70), 3-day (n = 70), and unstructured (n = 50) groups, respectively. Similar patterns of effects were found for changes in free-time physical activity and cardiovascular endurance. Incorporating a theory-based prediction model previously supported in teens through older adults, with and without medical disorders and health-risk factors, improvements in exercise-related self-regulation and self-efficacy, and mood, significantly predicted increased free-time physical activity (R² = .48). Effects significantly strengthened to R² = .62 when completion/non-completion of the recommended 300 min/week of physical activity was also accounted for. Change in BMI was inversely related to physical activity change, β=-.14, p < .05. The present evaluation process indicated promising effects, and indicated theory-based targets to foster future program improvements.     

Risk Perception and Information Processing: The Development and Validation of a Questionnaire to Assess Self‐Reported Information Processing

The role of information processing in understanding people's responses to risk information has recently received substantial attention. One limitation of this research concerns the unavailability of a validated questionnaire of information processing. This article presents two studies in which we describe the development and validation of the Information‐Processing Questionnaire to meet that need. Study 1 describes the development and initial validation of the questionnaire. Participants were randomized to either a systematic processing or a heuristic processing condition after which they completed a manipulation check and the initial 15‐item questionnaire and again two weeks later. The questionnaire was subjected to factor reliability and validity analyses on both measurement times for purposes of cross‐validation of the results. A two‐factor solution was observed representing a systematic processing and a heuristic processing subscale. The resulting scale showed good reliability and validity, with the systematic condition scoring significantly higher on the systematic subscale and the heuristic processing condition significantly higher on the heuristic subscale. Study 2 sought to further validate the questionnaire in a field study. Results of the second study corresponded with those of Study 1 and provided further evidence of the validity of the Information‐Processing Questionnaire. The availability of this information‐processing scale will be a valuable asset for future research and may provide researchers with new research opportunities.