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Many existing statistical and machine learning tools for social network analysis focus on a single level of analysis. Methods designed for clustering optimize a global partition of the graph, whereas projection-based approaches (e.g., the latent space model in the statistics literature) represent in rich detail the roles of individuals. Many pertinent questions in sociology and economics, however, span multiple scales of analysis. Further, many questions involve comparisons across disconnected graphs that will, inevitably be of different sizes, either due to missing data or the inherent heterogeneity in real-world networks. We propose a class of network models that represent network structure on multiple scales and facilitate comparison across graphs with different numbers of individuals. These models differentially invest modeling effort within subgraphs of high density, often termed communities, while maintaining a parsimonious structure between said subgraphs. We show that our model class is projective, highlighting an ongoing discussion in the social network modeling literature on the dependence of inference paradigms on the size of the observed graph. We illustrate the utility of our method using data on household relations from Karnataka, India. Supplementary material for this article is available online.

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OBJECTIVE: Explore the role of red blood cell donor sex on preterm infant neonatal outcomes. STUDY DESIGN: In a retrospective, exploratory, cohort study, the hospital blood bank database was queried for units of blood released to neonatal intensive care unit patients in 2009-2010. The state blood center provided donor sex, and a department database provided neonatal characteristics and morbidities. Comparisons were made for 2 groups: those who ever received female blood and those who did not. RESULTS: Among 462 infants <32 weeks of gestation, 190 (41%) received >1 blood transfusion. In univariate analyses, compared with infants who received only male blood, infants who received female donor blood had higher rates of bronchopulmonary dysplasia (38% vs 22%; P = .03), spontaneous intestinal perforation/necrotizing enterocolitis (17% vs 6%; P = .04), and death or any morbidity (60% vs 38%; P < .01), respectively. In adjusted analyses, female blood was associated with any morbidity (P = .0251) and 21 days longer hospitalization (P = .0098). After adding total number transfusions to the model, only an increased number of transfusions was associated with bronchopulmonary dysplasia (P = .0009), any morbidity (P = .0001), and length of stay (P = .0001). In subset regressions comparing exclusively female donor blood with male donor blood, there was a significant interaction of female donor blood and number of transfusions for any morbidity (OR 2.6 95% CI 1.2-5.7, P = .01). CONCLUSIONS: Preliminary findings suggest that female donor blood was associated with preterm vulnerability to neonatal morbidities.

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The objective of this research was to try to unveil the relationship between production traits and genotypic proportions of crossbred dairy cattle using principal component analysis (PCA) and cluster analysis. The herd consists of crossbred animals of Holstein (H) and Zebu (Z) (Gir and Guzerat) in different genotypic proportions; the composition of which varies from 12.5 to 100.0 % of the genetic group H. For this study, 834 milk production records from 257 cows from the years 1997 to 2014 were analyzed. The animals were all managed at a farm located in northeastern Brazil. The variables in the PCA were total milk yield per lactation (MY), milk yield adjusted to 305 days (MY305), lactation length (LL), and proportion of H and Z breeding. This analysis reduced the size of the sample space from the original five variables to two principal components (PCs) that together explained 89.4 % of the total variation. MY, MY305, LL, and genotypic proportion of H all contributed positively to PC1. The genotypic proportion of Z contributed negatively, which established a contrast between H and Z. Further cluster analysis identified two distinct groups when considering production performance and genotype of the animals. The high-performance group was predominantly Holstein breeding, while the lower performing group consisted mostly of Zebu. Under the environmental and management conditions in which this research was conducted, the best performances for the traits considered were achieved from cows whose genotypic proportion was between 38.0 and 94.0 % Holstein breeding.

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BACKGROUND: Deprivation indices are useful measures to analyze health inequalities. There are several methods to construct these indices, however, few studies have used Geographic Information Systems (GIS) and Multi-Criteria methods to construct a deprivation index. Therefore, this study applies Multi-Criteria Evaluation to calculate weights for the indicators that make up the deprivation index and a GIS-based fuzzy approach to create different scenarios of this index is also implemented. METHODS: The Analytical Hierarchy Process (AHP) is used to obtain the weights for the indicators of the index. The Ordered Weighted Averaging (OWA) method using linguistic quantifiers is applied in order to create different deprivation scenarios. Geographically Weighted Regression (GWR) and a Moran's I analysis are employed to explore spatial relationships between the different deprivation measures and two health factors: the distance to health services and the percentage of people that have never had a live birth. This last indicator was considered as the dependent variable in the GWR. The case study is Quito City, in Ecuador. RESULTS: The AHP-based deprivation index show medium and high levels of deprivation (0,511 to 1,000) in specific zones of the study area, even though most of the study area has low values of deprivation. OWA results show deprivation scenarios that can be evaluated considering the different attitudes of decision makers. GWR results indicate that the deprivation index and its OWA scenarios can be considered as local estimators for health related phenomena. Moran's I calculations demonstrate that several deprivation scenarios, in combination with the 'distance to health services' factor, could be explanatory variables to predict the percentage of people that have never had a live birth. CONCLUSIONS: The AHP-based deprivation index and the OWA deprivation scenarios developed in this study are Multi-Criteria instruments that can support the identification of highly deprived zones and can support health inequalities analysis in combination with different health factors. The methodology described in this study can be applied in other regions of the world to develop spatial deprivation indices based on Multi-Criteria analysis.

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Genotype by environment interaction (GxE) studies are of particular interest in Brazil because of the regional diversity of environmental effects and the wide variety of management systems. The present study evaluates GxE effects on 365 d weight (365W) of Nellore cattle raised on pasture in northern Brazil. The analysis utilized random regression techniques to model the reaction norm. Fixed effects consisted of sex, contemporary group, and the covariate of age of cow at calving. The environmental gradient, defined by the concatenation of a bull and the state in which the calf was born, was modeled by second order Legendre polynomials. Direct additive genetic and residual effects were fit as random. Results showed differences in the magnitude of expression of genotype in proportion to decreasing favorability of the environment. As the environment became more unfavorable, the correlation of breeding value to different environments decreased. The correlations between the intercept and the level slope for 365W feature were of moderate magnitude, predominantly indicating the reclassification of sires in different environments. Reaction standard model was coherent from a technical and biological view point and enabled the perception of GxE in the genetic evaluation of Nellore cattle in the states of Maranhão, Pará and Tocantins.

No Brasil, estudos de interações genótipo x ambiente tem atraído cada vez mais atenção em programas de melhoramento devido à variedade de sistemas de produção e à diversidade ambiental. Objetivou-se avaliar o efeito da interação genótipo x ambiente sobre o peso ajustado aos 365 dias de idade de bovinos da raça Nelore criados a pasto na região norte do Brasil. As análises foram realizadas utilizando-se regressão aleatória para modelar a norma de reação. Foi considerado como efeitos fixos o sexo, os grupos de contemporâneos e como covariável a idade da vaca ao parto. A gradiente ambiental, foi definida pela concatenação entre o touro e a respectiva unidade federativa de nascimento do animal, foi modelada por meio de polinômios de Legendre de segunda ordem. Como efeito aleatório, foram considerados os efeitos genéticos aditivos diretos e residuais. Os resultados demonstraram diferenças na magnitude da expressão de seu genótipo à proporção que o ambiente tornava-se desfavorável. Ou seja, à proporção que o ambiente torna-se desfavorável, menores seriam as correlações dos valores genéticos nos diferentes ambientes. As correlações entre o intercepto e o nível de inclinação da reta para a característica P365 foram de magnitude moderada, indicando predominantemente reclassificação dos valores genéticos dos animais nos diferentes ambientes. O modelo de norma de reação foi coerente doponto técnico e biológico de visualizar na avaliação genética da população Nelore criada nos Estados do Maranhão, Pará e Tocantins, a interação genótipo ambiente.

Assuntos

RESUMO

Genotype by environment interaction (GxE) studies are of particular interest in Brazil because of the regional diversity of environmental effects and the wide variety of management systems. The present study evaluates GxE effects on 365 d weight (365W) of Nellore cattle raised on pasture in northern Brazil. The analysis utilized random regression techniques to model the reaction norm. Fixed effects consisted of sex, contemporary group, and the covariate of age of cow at calving. The environmental gradient, defined by the concatenation of a bull and the state in which the calf was born, was modeled by second order Legendre polynomials. Direct additive genetic and residual effects were fit as random. Results showed differences in the magnitude of expression of genotype in proportion to decreasing favorability of the environment. As the environment became more unfavorable, the correlation of breeding value to different environments decreased. The correlations between the intercept and the level slope for 365W feature were of moderate magnitude, predominantly indicating the reclassification of sires in different environments. Reaction standard model was coherent from a technical and biological view point and enabled the perception of GxE in the genetic evaluation of Nellore cattle in the states of Maranhão, Pará and Tocantins.(AU) 

No Brasil, estudos de interações genótipo x ambiente tem atraído cada vez mais atenção em programas de melhoramento devido à variedade de sistemas de produção e à diversidade ambiental. Objetivou-se avaliar o efeito da interação genótipo x ambiente sobre o peso ajustado aos 365 dias de idade de bovinos da raça Nelore criados a pasto na região norte do Brasil. As análises foram realizadas utilizando-se regressão aleatória para modelar a norma de reação. Foi considerado como efeitos fixos o sexo, os grupos de contemporâneos e como covariável a idade da vaca ao parto. A gradiente ambiental, foi definida pela concatenação entre o touro e a respectiva unidade federativa de nascimento do animal, foi modelada por meio de polinômios de Legendre de segunda ordem. Como efeito aleatório, foram considerados os efeitos genéticos aditivos diretos e residuais. Os resultados demonstraram diferenças na magnitude da expressão de seu genótipo à proporção que o ambiente tornava-se desfavorável. Ou seja, à proporção que o ambiente torna-se desfavorável, menores seriam as correlações dos valores genéticos nos diferentes ambientes. As correlações entre o intercepto e o nível de inclinação da reta para a característica P365 foram de magnitude moderada, indicando predominantemente reclassificação dos valores genéticos dos animais nos diferentes ambientes. O modelo de norma de reação foi coerente doponto técnico e biológico de visualizar na avaliação genética da população Nelore criada nos Estados do Maranhão, Pará e Tocantins, a interação genótipo ambiente.(AU)

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