Maximum-likelihood estimation of the random-clumped multinomial model as a prototype problem for large-scale statistical computing

Numerical methods are needed to obtain maximum-likelihood estimates (MLEs) in many problems. Computation time can be an issue for some likelihoods even with modern computing power. We consider one such problem where the assumed model is a random-clumped multinomial distribution. We compute MLEs for this model in parallel using the Toolkit for Advanced Optimization software library. The computations are performed on a distributed-memory cluster with low latency interconnect. We demonstrate that for larger problems, scaling the number of processes improves wall clock time significantly. An illustrative example shows how parallel MLE computation can be useful in a large data analysis. Our experience with a direct numerical approach indicates that more substantial gains may be obtained by making use of the specific structure of the random-clumped model.     

Exploring spirituality among youth in foster care: findings from the Casey Field Office Mental Health Study

This study examined spiritual coping mechanisms, beliefs about spirituality and participation in spiritual activities and in other positive activities among adolescents in foster care. A multidimensional measure of spirituality was developed for face-to-face interviews with 188 youth (ages 14–17) from diverse racial/ethnic backgrounds in the United States. Findings revealed 95% of youth believe in God, over 70% believe God is 'creator' and God is 'love', and 79% considered prayer a spiritual practice. Most youth said love and forgiveness help them heal. Two-thirds (67%) reported responding to 'bad or tragic things happening' by spending time alone, and over half responded by praying (59%) or sharing the problem with someone else (56%). Youth's top three spiritual goals were to follow God's plan for them, become a better person, and know their purpose in life. Based on the value youth ascribed to spiritual coping mechanisms, recommendations for policy and practice focus on the integration of spirituality into practice and caregiving for youth in foster care.     

Understanding neighbourhoods, communities and environments: new approaches for social work research

This article discusses some new ways in which social work research can explore the interaction between neighbourhoods and child and adult wellbeing. The authors note that social work practices are often criticised for taking an individualistic approach and paying too little attention to the service user's environment. The article uses examples of research projects from Chile, the United States of America and Wales, to discuss the use of spatially oriented research methods for understanding neighbourhood factors. Quantitative, qualitative and mixed methods approaches that are particularly appropriate for investigating social work relevant topics are discussed in turn, including quantitative and qualitative uses for geographical information systems (GIS), hierarchical linear modelling (HLM) for analysing spatially clustered data and qualitative mobile interviews. The article continues with a discussion of the strengths and limitations of using spatially orientated research designs in social work research settings and concludes optimistically with suggestions for future directions in this area.     

Fulfilment of basic needs from a subjective point of view in rural Guatemala

Guardiola J, García‐Muñoz T. Fulfilment of basic needs from a subjective point of view in rural Guatemala Int J Soc Welfare 2011: 20: 393–403 © 2010 The Author(s), International Journal of Social Welfare © 2010 Blackwell Publishing Ltd and the International Journal of Social Welfare. The study of subjective wellbeing in developing countries is a relatively new field of research, but interest is increasing among researchers. A few decades ago, techniques such as the basic needs approach were applied in order to understand development. The basic needs framework has recently been used to define and monitor the Millennium Development Goals. However, it is limited when it comes to defining the content of basic needs and determining to what extent they are being satisfied, which leaves this decision to an external authority other than the individual. In this article, we estimated how certain indicators and assets have influenced the perception of basic needs in a rural area of Guatemala using a data set containing 369 interviews with Mayan households. The results allowed us to identify the characteristics or assets that influence the perception of basic needs, leaving the decision as to the Mayan people themselves as to whether their basic needs are being met.     

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States,Italy, Spain,and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.     

Metrics and barycenters for point pattern data

We introduce the transport–transform and the relative transport–transform metrics between finite point patterns on a general space, which provide a unified framework for earlier point pattern metrics, in particular the generalized spike time and the normalized and unnormalized optimal subpattern assignment metrics. Our main focus is on barycenters, i.e., minimizers of a q-th-order Fréchet functional with respect to these metrics. We present a heuristic algorithm that terminates in a local minimum and is shown to be fast and reliable in a simulation study. The algorithm serves as a general plug-in method that can be applied to point patterns on any state space where an appropriate algorithm for solving the location problem for individual points is available. We present applications to geocoded data of crimes in Euclidean space and on a street network, illustrating that barycenters serve as informative summary statistics. Our work is a first step toward statistical inference in covariate-based models of repeated point pattern observations.     

Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation

A perturbative approach is used to derive approximations of arbitrary order to estimate high percentiles of sums of positive independent random variables that exhibit heavy tails. Closed-form expressions for the successive approximations are obtained both when the number of terms in the sum is deterministic and when it is random. The zeroth order approximation is the percentile of the maximum term in the sum. Higher orders in the perturbative series involve the right-truncated moments of the individual random variables that appear in the sum. These censored moments are always finite. As a result, and in contrast to previous approximations proposed in the literature, the perturbative series has the same form regardless of whether these random variables have a finite mean or not. For high percentiles, and specially for heavier tails, the quality of the estimate improves as more terms are included in the series, up to a certain order. Beyond that order the convergence of the series deteriorates. Nevertheless, the approximations obtained by truncating the perturbative series at intermediate orders are remarkably accurate for a variety of distributions in a wide range of parameters.     

Life Satisfaction in Brazil: Testing the Psychometric Properties of the Satisfaction With Life Scale (SWLS) in Five Brazilian Samples

The aim of this paper was to validate the Brazilian-Portuguese version of the Satisfaction With Life Scale (SWLS), presenting evidence of its reliability and construct and criterion-related validity. A large Brazilian sample (2,180 participants), from five different populations (undergraduate and high school students, general population, elementary school teachers, and physicians), was considered. The results confirmed the single factorial structure and reliability (0.77 < Cronbach’s α < 0.88, mean α = 0.81) of the SWLS. Supporting its criterion-related validity, the SWLS correlated positively with positive affect and negatively with both negative affect and psychological distress across all five samples. The findings indicate that the Brazilian-Portuguese version of the SWLS is a valid instrument to use with diverse Brazilian samples.     

Undercounting Urban Residents in Bolivia: A Small-Area Study of Census-Driven Migration

Employing a small-area study approach in a single urban area in Bolivia, a country with high rates of internal circular migration, we describe how, in the months before the November 2012 census, local leaders and neighbors, concerned with maximizing the per capita resources their residential districts and rural communities could claim from central government, threatened to employ sanctions against absent individuals whom they judged to be regular residents. We use three types of data—a two-wave household survey, data from vehicle toll booths, and photographic logs of a minibus station—to show how these threats generated substantial movement out of the urban area, leading to an urban undercount of roughly 20 % of prime-age adults and 50 % of those aged at least 50. More generally, we argue that these data highlight how local leaders’ increasingly sophisticated attempts to shape data extend beyond the well-known examples from autocratic states. This is driven by a combination of intensive urban–rural connections, leaders’ greater democratic accountability to local voters, increasing fiscal transparency at the national level, increasing fiscal accountability of governments to transnational neoliberal institutions pushing “transparency” and “evidence-based” policy, and more overt talk about “resource sharing” that is rooted in an evidence-based planning paradigm. Since these structural conditions exist in many other developing countries, the possibility of equivalent urban undercounts in forthcoming censuses needs to be anticipated and avoided.