Spatial Cluster Detection for Longitudinal Outcomes Using Administrative Regions

This article proposes a new spatial cluster detection method for longitudinal outcomes that detects neighborhoods and regions with elevated rates of disease while controlling for individual level confounders. The proposed method, CumResPerm, utilizes cumulative geographic residuals through a permutation test to detect potential clusters which are defined as sets of administrative regions, such as a town or group of administrative regions. Previous cluster detection methods are not able to incorporate individual level data including covariate adjustment, while still being able to define potential clusters using informative neighborhood or town boundaries. Often, it is of interest to detect such spatial clusters because individuals residing in a town may have similar environmental exposures or socioeconomic backgrounds due to administrative reasons, such as zoning laws. Therefore, these boundaries can be very informative and more relevant than arbitrary clusters such as the standard circle or square. Application of the CumResPerm method will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between area or neighborhood residence and repeated measured outcome, occurrence of wheeze in the last six months, while taking into account mobile locations.     

“A Second-Chance at Being a Parent”: Grandparent Caregivers’ Reported Communication and Parenting Practices with Co-Residential Grandchildren

ABSTRACT

Grandfamilies, family structures in which grandparent(s) co-reside with and assume a primary caregiving role for at least one grandchild, are increasingly common in the United States. This qualitative, exploratory study, informed by family communication patterns theory (FCPT), illuminated the reported communication beliefs and practices of grandparents who serve as primary caregiver to at least one grandchild. Hybrid thematic analysis, combining FCTP with inductive analysis, was used to analyze 21 semi-structured interviews with grandparents. Results yielded four themes describing grandparents’ reported communicative practices: creating opportunities for listening and dialogue, talking about emotion, emphasizing openness, and allowing questioning; and three themes describing the impact of second-chance parenting: increased resources, acquired wisdom, and matured emotionally. Implications for grandfamily communication research in light of hybrid analyses and FCPT are discussed.     

A new mixture model on the simplex

This paper is meant to introduce a significant extension of the flexible Dirichlet (FD) distribution, which is a quite tractable special mixture model for compositional data, i.e. data representing vectors of proportions of a whole. The FD model displays several theoretical properties which make it suitable for inference, and fairly easy to handle from a computational viewpoint. However, the rigid type of mixture structure implied by the FD makes it unsuitable to describe many compositional datasets. Furthermore, the FD only allows for negative correlations. The new extended model, by considerably relaxing the strict constraints among clusters entailed by the FD, allows for a more general dependence structure (including positive correlations) and greatly expands its applicative potential. At the same time, it retains, to a large extent, its good properties. EM-type estimation procedures can be developed for this more complex model, including ad hoc reliable initialization methods, which permit to keep the computational issues at a rather uncomplicated level. Accurate evaluation of standard error estimates can be provided as well.     

BANKS,DEBT AND RISK: ASSESSING THE SPILLOVERS OF CORPORATE TAXES

We find evidence of tax-driven strategic allocation of debt and asset risk across group entities of European banks. We evaluate the effects that establishing tax neutrality between debt and equity finance has on systemic risk, and show that the degree of coordination in implementing the hypothetical tax reform matters. In particular, a coordinated elimination of the tax advantage of debt would significantly reduce systemic losses in the event of a severe banking crisis. By contrast, uncoordinated tax reforms are not equally beneficial precisely because national tax policies generate spillovers through cross-border bank activities. (JEL G21, G28, H25)     

Retrospective Paternal and Maternal Parenting Styles,Regulatory Self-Efficacy and Adolescent Risk Taking

This study aims to calculate a scaled risk-taking behavior index and to test a model in which maternal and paternal parenting styles affect risk-taking behavior with a mediation of adolescents’ regulatory self-efficacy. Participants were 816 adolescents (44% males) responding to a self-report questionnaire about their risk-taking behavior, regulatory self-efficacy, and retrospective memories of paternal and maternal parenting styles. Results suggested an item rating in the index showing that behaviors considered less risky referred to alcohol use and the unplanned first sexual intercourse, whereas behaviors considered more risky referred to the lack of use of contraceptives and the age of the first sexual intercourse. Results revealed a significant indirect effect of authoritative and authoritarian styles on risk-taking behavior. These styles shaped the adolescents’ regulatory self-efficacy, which in turn predicted adolescent risk-taking behavior. Results underline the complex interplay of relationships between parents and their children.     

Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

Clustering transformed compositional data using K-means,with applications in gene expression and bicycle sharing system data

Although there is no shortage of clustering algorithms proposed in the literature, the question of the most relevant strategy for clustering compositional data (i.e. data whose rows belong to the simplex) remains largely unexplored in cases where the observed value is equal or close to zero for one or more samples. This work is motivated by the analysis of two applications, both focused on the categorization of compositional profiles: (1) identifying groups of co-expressed genes from high-throughput RNA sequencing data, in which a given gene may be completely silent in one or more experimental conditions; and (2) finding patterns in the usage of stations over the course of one week in the Velib' bicycle sharing system in Paris, France. For both of these applications, we make use of appropriately chosen data transformations, including the Centered Log Ratio and a novel extension called the Log Centered Log Ratio, in conjunction with the K-means algorithm. We use a non-asymptotic penalized criterion, whose penalty is calibrated with the slope heuristics, to select the number of clusters. Finally, we illustrate the performance of this clustering strategy, which is implemented in the Bioconductor package coseq, on both the gene expression and bicycle sharing system data.