962 resultados para multilevel hierarchical models
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When choosing among models to describe categorical data, the necessity to consider interactions makes selection more difficult. With just four variables, considering all interactions, there are 166 different hierarchical models and many more non-hierarchical models. Two procedures have been developed for categorical data which will produce the "best" subset or subsets of each model size where size refers to the number of effects in the model. Both procedures are patterned after the Leaps and Bounds approach used by Furnival and Wilson for continuous data and do not generally require fitting all models. For hierarchical models, likelihood ratio statistics (G('2)) are computed using iterative proportional fitting and "best" is determined by comparing, among models with the same number of effects, the Pr((chi)(,k)('2) (GREATERTHEQ) G(,ij)('2)) where k is the degrees of freedom for ith model of size j. To fit non-hierarchical as well as hierarchical models, a weighted least squares procedure has been developed.^ The procedures are applied to published occupational data relating to the occurrence of byssinosis. These results are compared to previously published analyses of the same data. Also, the procedures are applied to published data on symptoms in psychiatric patients and again compared to previously published analyses.^ These procedures will make categorical data analysis more accessible to researchers who are not statisticians. The procedures should also encourage more complex exploratory analyses of epidemiologic data and contribute to the development of new hypotheses for study. ^
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Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.
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La creciente complejidad, heterogeneidad y dinamismo inherente a las redes de telecomunicaciones, los sistemas distribuidos y los servicios avanzados de información y comunicación emergentes, así como el incremento de su criticidad e importancia estratégica, requieren la adopción de tecnologías cada vez más sofisticadas para su gestión, su coordinación y su integración por parte de los operadores de red, los proveedores de servicio y las empresas, como usuarios finales de los mismos, con el fin de garantizar niveles adecuados de funcionalidad, rendimiento y fiabilidad. Las estrategias de gestión adoptadas tradicionalmente adolecen de seguir modelos excesivamente estáticos y centralizados, con un elevado componente de supervisión y difícilmente escalables. La acuciante necesidad por flexibilizar esta gestión y hacerla a la vez más escalable y robusta, ha provocado en los últimos años un considerable interés por desarrollar nuevos paradigmas basados en modelos jerárquicos y distribuidos, como evolución natural de los primeros modelos jerárquicos débilmente distribuidos que sucedieron al paradigma centralizado. Se crean así nuevos modelos como son los basados en Gestión por Delegación, en el paradigma de código móvil, en las tecnologías de objetos distribuidos y en los servicios web. Estas alternativas se han mostrado enormemente robustas, flexibles y escalables frente a las estrategias tradicionales de gestión, pero continúan sin resolver aún muchos problemas. Las líneas actuales de investigación parten del hecho de que muchos problemas de robustez, escalabilidad y flexibilidad continúan sin ser resueltos por el paradigma jerárquico-distribuido, y abogan por la migración hacia un paradigma cooperativo fuertemente distribuido. Estas líneas tienen su germen en la Inteligencia Artificial Distribuida (DAI) y, más concretamente, en el paradigma de agentes autónomos y en los Sistemas Multi-agente (MAS). Todas ellas se perfilan en torno a un conjunto de objetivos que pueden resumirse en alcanzar un mayor grado de autonomía en la funcionalidad de la gestión y una mayor capacidad de autoconfiguración que resuelva los problemas de escalabilidad y la necesidad de supervisión presentes en los sistemas actuales, evolucionar hacia técnicas de control fuertemente distribuido y cooperativo guiado por la meta y dotar de una mayor riqueza semántica a los modelos de información. Cada vez más investigadores están empezando a utilizar agentes para la gestión de redes y sistemas distribuidos. Sin embargo, los límites establecidos en sus trabajos entre agentes móviles (que siguen el paradigma de código móvil) y agentes autónomos (que realmente siguen el paradigma cooperativo) resultan difusos. Muchos de estos trabajos se centran en la utilización de agentes móviles, lo cual, al igual que ocurría con las técnicas de código móvil comentadas anteriormente, les permite dotar de un mayor componente dinámico al concepto tradicional de Gestión por Delegación. Con ello se consigue flexibilizar la gestión, distribuir la lógica de gestión cerca de los datos y distribuir el control. Sin embargo se permanece en el paradigma jerárquico distribuido. Si bien continúa sin definirse aún una arquitectura de gestión fiel al paradigma cooperativo fuertemente distribuido, estas líneas de investigación han puesto de manifiesto serios problemas de adecuación en los modelos de información, comunicación y organizativo de las arquitecturas de gestión existentes. En este contexto, la tesis presenta un modelo de arquitectura para gestión holónica de sistemas y servicios distribuidos mediante sociedades de agentes autónomos, cuyos objetivos fundamentales son el incremento del grado de automatización asociado a las tareas de gestión, el aumento de la escalabilidad de las soluciones de gestión, soporte para delegación tanto por dominios como por macro-tareas, y un alto grado de interoperabilidad en entornos abiertos. A partir de estos objetivos se ha desarrollado un modelo de información formal de tipo semántico, basado en lógica descriptiva que permite un mayor grado de automatización en la gestión en base a la utilización de agentes autónomos racionales, capaces de razonar, inferir e integrar de forma dinámica conocimiento y servicios conceptualizados mediante el modelo CIM y formalizados a nivel semántico mediante lógica descriptiva. El modelo de información incluye además un “mapping” a nivel de meta-modelo de CIM al lenguaje de especificación de ontologías OWL, que supone un significativo avance en el área de la representación y el intercambio basado en XML de modelos y meta-información. A nivel de interacción, el modelo aporta un lenguaje de especificación formal de conversaciones entre agentes basado en la teoría de actos ilocucionales y aporta una semántica operacional para dicho lenguaje que facilita la labor de verificación de propiedades formales asociadas al protocolo de interacción. Se ha desarrollado también un modelo de organización holónico y orientado a roles cuyas principales características están alineadas con las demandadas por los servicios distribuidos emergentes e incluyen la ausencia de control central, capacidades de reestructuración dinámica, capacidades de cooperación, y facilidades de adaptación a diferentes culturas organizativas. El modelo incluye un submodelo normativo adecuado al carácter autónomo de los holones de gestión y basado en las lógicas modales deontológica y de acción.---ABSTRACT---The growing complexity, heterogeneity and dynamism inherent in telecommunications networks, distributed systems and the emerging advanced information and communication services, as well as their increased criticality and strategic importance, calls for the adoption of increasingly more sophisticated technologies for their management, coordination and integration by network operators, service providers and end-user companies to assure adequate levels of functionality, performance and reliability. The management strategies adopted traditionally follow models that are too static and centralised, have a high supervision component and are difficult to scale. The pressing need to flexibilise management and, at the same time, make it more scalable and robust recently led to a lot of interest in developing new paradigms based on hierarchical and distributed models, as a natural evolution from the first weakly distributed hierarchical models that succeeded the centralised paradigm. Thus new models based on management by delegation, the mobile code paradigm, distributed objects and web services came into being. These alternatives have turned out to be enormously robust, flexible and scalable as compared with the traditional management strategies. However, many problems still remain to be solved. Current research lines assume that the distributed hierarchical paradigm has as yet failed to solve many of the problems related to robustness, scalability and flexibility and advocate migration towards a strongly distributed cooperative paradigm. These lines of research were spawned by Distributed Artificial Intelligence (DAI) and, specifically, the autonomous agent paradigm and Multi-Agent Systems (MAS). They all revolve around a series of objectives, which can be summarised as achieving greater management functionality autonomy and a greater self-configuration capability, which solves the problems of scalability and the need for supervision that plague current systems, evolving towards strongly distributed and goal-driven cooperative control techniques and semantically enhancing information models. More and more researchers are starting to use agents for network and distributed systems management. However, the boundaries established in their work between mobile agents (that follow the mobile code paradigm) and autonomous agents (that really follow the cooperative paradigm) are fuzzy. Many of these approximations focus on the use of mobile agents, which, as was the case with the above-mentioned mobile code techniques, means that they can inject more dynamism into the traditional concept of management by delegation. Accordingly, they are able to flexibilise management, distribute management logic about data and distribute control. However, they remain within the distributed hierarchical paradigm. While a management architecture faithful to the strongly distributed cooperative paradigm has yet to be defined, these lines of research have revealed that the information, communication and organisation models of existing management architectures are far from adequate. In this context, this dissertation presents an architectural model for the holonic management of distributed systems and services through autonomous agent societies. The main objectives of this model are to raise the level of management task automation, increase the scalability of management solutions, provide support for delegation by both domains and macro-tasks and achieve a high level of interoperability in open environments. Bearing in mind these objectives, a descriptive logic-based formal semantic information model has been developed, which increases management automation by using rational autonomous agents capable of reasoning, inferring and dynamically integrating knowledge and services conceptualised by means of the CIM model and formalised at the semantic level by means of descriptive logic. The information model also includes a mapping, at the CIM metamodel level, to the OWL ontology specification language, which amounts to a significant advance in the field of XML-based model and metainformation representation and exchange. At the interaction level, the model introduces a formal specification language (ACSL) of conversations between agents based on speech act theory and contributes an operational semantics for this language that eases the task of verifying formal properties associated with the interaction protocol. A role-oriented holonic organisational model has also been developed, whose main features meet the requirements demanded by emerging distributed services, including no centralised control, dynamic restructuring capabilities, cooperative skills and facilities for adaptation to different organisational cultures. The model includes a normative submodel adapted to management holon autonomy and based on the deontic and action modal logics.
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O objetivo dessa pesquisa foi avaliar aspectos genéticos que relacionados à produção in vitro de embriões na raça Guzerá. O primeiro estudo focou na estimação de (co) variâncias genéticas e fenotípicas em características relacionadas a produção de embriões e na detecção de possível associação com a idade ao primeiro parto (AFC). Foi detectada baixa e média herdabilidade para características relacionadas à produção de oócitos e embriões. Houve fraca associação genética entre características ligadas a reprodução artificial e a idade ao primeiro parto. O segundo estudo avaliou tendências genéticas e de endogamia em uma população Guzerá no Brasil. Doadoras e embriões produzidos in vitro foram considerados como duas subpopulações de forma a realizar comparações acerca das diferenças de variação anual genética e do coeficiente de endogamia. A tendência anual do coeficiente de endogamia (F) foi superior para a população geral, sendo detectado efeito quadrático. No entanto, a média de F para a sub- população de embriões foi maior do que na população geral e das doadoras. Foi observado ganho genético anual superior para a idade ao primeiro parto e para a produção de leite (305 dias) entre embriões produzidos in vitro do que entre doadoras ou entre a população geral. O terceiro estudo examinou os efeitos do coeficiente de endogamia da doadora, do reprodutor (usado na fertilização in vitro) e dos embriões sobre resultados de produção in vitro de embriões na raça Guzerá. Foi detectado efeito da endogamia da doadora e dos embriões sobre as características estudadas. O quarto (e último) estudo foi elaborado para comparar a adequação de modelos mistos lineares e generalizados sob método de Máxima Verossimilhança Restrita (REML) e sua adequação a variáveis discretas. Quatro modelos hierárquicos assumindo diferentes distribuições para dados de contagem encontrados no banco. Inferência foi realizada com base em diagnósticos de resíduo e comparação de razões entre componentes de variância para os modelos em cada variável. Modelos Poisson superaram tanto o modelo linear (com e sem transformação da variável) quanto binomial negativo à qualidade do ajuste e capacidade preditiva, apesar de claras diferenças observadas na distribuição das variáveis. Entre os modelos testados, a pior qualidade de ajuste foi obtida para o modelo linear mediante transformação logarítmica (Log10 X +1) da variável resposta.
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Introdução: Estudos recentes têm mostrado que as quedas são a causa externa de morte mais importante entre idosos, podendo levar a hospitalização, lesões, dependência e aumento nos custos dos serviços sociais e de saúde. O comprometimento da mobilidade funcional é um importante fator de risco para quedas, mas aspectos sociais, ambientais e comportamentais também podem influenciar nesse evento. Objetivo: Identificar os aspectos socioeconômicos e contextuais associados com a mobilidade funcional e quedas em idosos residentes no município de São Paulo. Métodos: Foram utilizados os dados do Estudo Saúde, Bem-Estar e Envelhecimento (SABE), uma amostra representativa para os indivíduos com idade igual ou superior a 60 anos do município de São Paulo, em 2010. As variáveis dependentes do estudo foram a ocorrência de alguma queda no último ano e o comprometimento da mobilidade funcional, mensurada pelo teste Timed Up and Go (TUG). Fatores individuais (estado marital, raça/cor, anos de estudo e percepção de suficiência de renda) e contextuais (Índice de Gini, área verde/ habitante, taxa de homicídio e percentual de domicílios em favelas) foram analisados por modelos logísticos multiníveis. Resultados: De 1.190 idosos inclusos, 29 por cento relataram ter caído no último ano e 46 por cento apresentaram comprometimento da mobilidade funcional. Os fatores individuais socioeconômicos não apresentaram associação com a ocorrência de queda, mas ter 8 anos ou mais de anos de estudo foi um fator protetor para comprometimento da mobilidade em todos os modelos testados (OR: 0,56). Morar em subprefeituras com taxa de homicídio moderada apresentou associação com chance aumentada de cair (OR: 1.51, 95 por cento IC: 1.09-2.07). Moderada área verde se associou com maior chance de cair entre os indivíduos com 80 anos e mais (OR:2,63, 95 por cento IC: 1.23-5.60). Conclusão: Os resultados estão de acordo com a literatura em relação à associação das características do bairro de residência com quedas e mobilidade funcional em idosos. Estratégias voltadas para prevenção de quedas e de dificuldade na mobilidade funcional devem considerar aspectos sociais e ambientais de locais públicos. Este estudo foi financiado pela Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (nº processo: 2014/06721-4)
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Thesis (Ph.D.)--University of Washington, 2016-06
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While the carnivores are considered regulators and structuring of natural communities are also extremely threatened by human activities. Endangered little-spotted-cat (Leopardus tigrinus) is one of the lesser known species from the Neotropical cats. In this work we investigate the occupancy and the activity pattern of L. tigrinus in Caatinga of Rio Grande do Norte testing: 1) how environmental and anthropogenic factors influence their occupation and 2) how biotic and abiotic factors influence their activity pattern. For this we raised occurrence data of species in 10 priority areas for conservation. We built hierarchical models of occupancy based on maximum likelihood to represent biological hypotheses which were ranked using the Akaike Information Criterion (AIC). According to the results the feline occupancy is more likely away from rural settlements and in areas with a higher proportion of woody vegetation. The opportunistic killing of L. tigrinus and in retaliation for poultry predation close to residential areas can explain this result; as well as more complex vegetation structure can better serve as refuge and ensure more food. Analyzing the records of the species through circular statistics we conclude that the activity pattern is mostly nocturnal, although considerable crepuscular and a small diurnal activity. L. tigrinus activity was directly affected by the availability of small terrestrial mammals, which are essentially nocturnal. In addition, the temperatures recorded in the environment directly and indirectly affect the activity of the little-spotted-cat, as also influence the activity of their potential prey. Generally, the cats were more active when possible prey were active, and this happened at night when lower temperatures are recorded. Moreover, the different lunar phases did not affect the activity pattern. The results improve the understanding of an endangered feline inhabiting the Caatinga biome, and thus can help develop conservation and management strategies, as well as in planning future research in this semi-arid ecosystem.
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Background
Learning to read is a key goal during primary school: reading difficulties may curtail children’s learning trajectories. Controversy remains regarding what types of interventions are effective for children at risk for academic failure, such as children in disadvantaged areas. We present data from a complex intervention to test the hypothesis that phonic skills and word recognition abilities are a pivotal and specific causal mechanism for the development of reading skills in children at risk for poorer literacy outcomes.
Method
Over 500 pupils across 16 primary schools took part in a Cluster Randomised Controlled Trial from school year 1 to year 3. Schools were randomly allocated to the intervention or the control arm. The intervention involved a literacy-rich after-school programme. Children attending schools in the control arm of the study received the curriculum normally provided. Children in both arms completed batteries of language, phonic skills, and reading tests every year. We used multilevel mediation models to investigate mediating processes between intervention and outcomes.
Findings
Children who took part in the intervention displayed improvements in reading skills compared to those in the control arm. Results indicated a significant indirect effect of the intervention via phonics encoding.
Discussion
The results suggest that the intervention was effective in improving reading abilities of children at risk, and this effect was mediated by improving children’s phonic skills. This has relevance for designing interventions aimed at improving literacy skills of children exposed to socio-economic disadvantage. Results also highlight the importance of methods to investigate causal pathways from intervention to outcomes.
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Temporal replicate counts are often aggregated to improve model fit by reducing zero-inflation and count variability, and in the case of migration counts collected hourly throughout a migration, allows one to ignore nonindependence. However, aggregation can represent a loss of potentially useful information on the hourly or seasonal distribution of counts, which might impact our ability to estimate reliable trends. We simulated 20-year hourly raptor migration count datasets with known rate of change to test the effect of aggregating hourly counts to daily or annual totals on our ability to recover known trend. We simulated data for three types of species, to test whether results varied with species abundance or migration strategy: a commonly detected species, e.g., Northern Harrier, Circus cyaneus; a rarely detected species, e.g., Peregrine Falcon, Falco peregrinus; and a species typically counted in large aggregations with overdispersed counts, e.g., Broad-winged Hawk, Buteo platypterus. We compared accuracy and precision of estimated trends across species and count types (hourly/daily/annual) using hierarchical models that assumed a Poisson, negative binomial (NB) or zero-inflated negative binomial (ZINB) count distribution. We found little benefit of modeling zero-inflation or of modeling the hourly distribution of migration counts. For the rare species, trends analyzed using daily totals and an NB or ZINB data distribution resulted in a higher probability of detecting an accurate and precise trend. In contrast, trends of the common and overdispersed species benefited from aggregation to annual totals, and for the overdispersed species in particular, trends estimating using annual totals were more precise, and resulted in lower probabilities of estimating a trend (1) in the wrong direction, or (2) with credible intervals that excluded the true trend, as compared with hourly and daily counts.
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Cette thèse de doctorat s’intéresse à mieux comprendre, d’une part, ce qui influence la sécrétion de cortisol salivaire, et d’autre part, ce qui influence l’épuisement professionnel. Plusieurs objectifs en découlent. D’abord, elle vise à mieux cerner la contribution des conditions de l’organisation du travail (utilisation des compétences, autorité décisionnelle, demandes psychologiques, demandes physiques, horaire de travail irrégulier, nombre d’heures travaillées, soutien social des collègues, soutien social des superviseurs, insécurité d’emploi) sur la sécrétion de cortisol salivaire, ainsi que le rôle modérateur de certains traits de personnalité (extraversion, agréabilité, névrosisme, conscience, ouverture d’esprit, estime de soi, centre de contrôle) sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Par ailleurs, cette thèse vise à établir la contribution des conditions de l’organisation du travail sur l’épuisement professionnel, ainsi que le rôle modérateur des traits de personnalité sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. Finalement, cette thèse vise à vérifier si la sécrétion de cortisol salivaire joue un rôle médiateur sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel, ainsi qu’à identifier les effets de médiation modérés par les traits de personnalité sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Ces objectifs sont inspirés de nombreuses limites observées dans la littérature, principalement l’intégration de déterminants à la fois biologiques, psychologiques et du travail dans la compréhension de l’épuisement professionnel. La thèse propose un modèle conceptuel qui tente de savoir comment ces différents stresseurs entraînent une dérégulation de la sécrétion de cortisol dans la salive des travailleurs. Ensuite, ce modèle conceptuel vise à voir si cette dérégulation s’associe à l’épuisement professionnel. Finalement, ce modèle conceptuel cherche à expliquer comment la personnalité peut influencer la manière dont ces variables sont reliées entre elles, c’est-à-dire de voir si la personnalité joue un rôle modérateur. Ce modèle découle de quatre théories particulières, notamment la perspective biologique de Selye (1936). Les travaux de Selye s’orientent sur l’étude de la réaction physiologique d’un organisme soumis à un stresseur. Dans ces circonstances, l’organisme est en perpétuel effort de maintien de son équilibre (homéostasie) et ne tolère que très peu de modifications à cet équilibre. En cas de modifications excessives, une réponse de stress est activée afin d’assurer l’adaptation en maintenant l’équilibre de base de l’organisme. Ensuite, le modèle conceptuel s’appuie sur le modèle de Lazarus et Folkman (1984) qui postule que la réponse de stress dépend plutôt de l’évaluation que font les individus de la situation stressante, et également sur le modèle de Pearlin (1999) qui postule que les individus exposés aux mêmes stresseurs ne sont pas nécessairement affectés de la même manière. Finalement, le modèle conceptuel de cette thèse s’appuie sur le modèle de Marchand (2004) qui postule que les réactions dépendent du décodage que font les acteurs des contraintes et ressources qui les affectent. Diverses hypothèses émergent de cette conceptualisation théorique. La première est que les conditions de l’organisation du travail contribuent directement aux variations de la sécrétion de cortisol salivaire. La deuxième est que les conditions de l’organisation du travail contribuent directement à l’épuisement professionnel. La troisième est que la sécrétion de cortisol salivaire médiatise la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. La quatrième est que la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire est modérée par les traits de personnalité. La cinquième est que la relation entre les conditions de l’organisation du travail, la sécrétion de cortisol salivaire et l’épuisement professionnel est modérée par les traits de personnalité. Des modèles de régression multiniveaux et des analyses de cheminement de causalité ont été effectués sur un échantillon de travailleurs canadiens provenant de l’étude SALVEO. Les résultats obtenus sont présentés sous forme de trois articles, soumis pour publication, lesquels constituent les chapitres 4 à 6 de cette thèse. Dans l’ensemble, le modèle intégrateur biopsychosocial proposé dans le cadre de cette thèse de doctorat permet de mieux saisir la complexité de l’épuisement professionnel qui trouve une explication biologique, organisationnelle et individuelle. Ce constat permet d’offrir une compréhension élargie et multiniveaux et assure l’avancement des connaissances sur une problématique préoccupante pour les organisations, la société ainsi que pour les travailleurs. Effectivement, la prise en compte des traits de personnalité et de la sécrétion du cortisol salivaire dans l’étude de l’épuisement professionnel assure une analyse intégrée et plus objective. Cette thèse conclue sur les implications de ces résultats pour la recherche, et sur les retombées qui en découlent pour les milieux de travail.
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La connectomique est l’étude des cartes de connectivité du cerveau (animal ou humain), qu’on nomme connectomes. À l’aide des outils développés par la science des réseaux complexes, la connectomique tente de décrire la complexité fonctionnelle et structurelle du cerveau. L’organisation des connexions du connectome, particulièrement la hiérarchie sous-jacente, joue un rôle majeur. Jusqu’à présent, les modèles hiérarchiques utilisés en connectomique sont pauvres en propriétés émergentes et présentent des structures régulières. Or, la complexité et la richesse hiérarchique du connectome et de réseaux réels ne sont pas saisies par ces modèles. Nous introduisons un nouveau modèle de croissance de réseaux hiérarchiques basé sur l’attachement préférentiel (HPA - Hierarchical preferential attachment). La calibration du modèle sur les propriétés structurelles de réseaux hiérarchiques réels permet de reproduire plusieurs propriétés émergentes telles que la navigabilité, la fractalité et l’agrégation. Le modèle permet entre autres de contrôler la structure hiérarchique et apporte un support supplémentaire quant à l’influence de la structure sur les propriétés émergentes. Puisque le cerveau est continuellement en activité, nous nous intéressons également aux propriétés dynamiques sur des structures hiérarchiques produites par HPA. L’existence d’états dynamiques d’activité soutenue, analogues à l’état minimal de l’activité cérébrale, est étudiée en imposant une dynamique neuronale binaire. Bien que l’organisation hiérarchique favorise la présence d’un état d’activité minimal, l’activité persistante émerge du contrôle de la propagation par la structure du réseau.
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Cette thèse de doctorat s’intéresse à mieux comprendre, d’une part, ce qui influence la sécrétion de cortisol salivaire, et d’autre part, ce qui influence l’épuisement professionnel. Plusieurs objectifs en découlent. D’abord, elle vise à mieux cerner la contribution des conditions de l’organisation du travail (utilisation des compétences, autorité décisionnelle, demandes psychologiques, demandes physiques, horaire de travail irrégulier, nombre d’heures travaillées, soutien social des collègues, soutien social des superviseurs, insécurité d’emploi) sur la sécrétion de cortisol salivaire, ainsi que le rôle modérateur de certains traits de personnalité (extraversion, agréabilité, névrosisme, conscience, ouverture d’esprit, estime de soi, centre de contrôle) sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Par ailleurs, cette thèse vise à établir la contribution des conditions de l’organisation du travail sur l’épuisement professionnel, ainsi que le rôle modérateur des traits de personnalité sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. Finalement, cette thèse vise à vérifier si la sécrétion de cortisol salivaire joue un rôle médiateur sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel, ainsi qu’à identifier les effets de médiation modérés par les traits de personnalité sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Ces objectifs sont inspirés de nombreuses limites observées dans la littérature, principalement l’intégration de déterminants à la fois biologiques, psychologiques et du travail dans la compréhension de l’épuisement professionnel. La thèse propose un modèle conceptuel qui tente de savoir comment ces différents stresseurs entraînent une dérégulation de la sécrétion de cortisol dans la salive des travailleurs. Ensuite, ce modèle conceptuel vise à voir si cette dérégulation s’associe à l’épuisement professionnel. Finalement, ce modèle conceptuel cherche à expliquer comment la personnalité peut influencer la manière dont ces variables sont reliées entre elles, c’est-à-dire de voir si la personnalité joue un rôle modérateur. Ce modèle découle de quatre théories particulières, notamment la perspective biologique de Selye (1936). Les travaux de Selye s’orientent sur l’étude de la réaction physiologique d’un organisme soumis à un stresseur. Dans ces circonstances, l’organisme est en perpétuel effort de maintien de son équilibre (homéostasie) et ne tolère que très peu de modifications à cet équilibre. En cas de modifications excessives, une réponse de stress est activée afin d’assurer l’adaptation en maintenant l’équilibre de base de l’organisme. Ensuite, le modèle conceptuel s’appuie sur le modèle de Lazarus et Folkman (1984) qui postule que la réponse de stress dépend plutôt de l’évaluation que font les individus de la situation stressante, et également sur le modèle de Pearlin (1999) qui postule que les individus exposés aux mêmes stresseurs ne sont pas nécessairement affectés de la même manière. Finalement, le modèle conceptuel de cette thèse s’appuie sur le modèle de Marchand (2004) qui postule que les réactions dépendent du décodage que font les acteurs des contraintes et ressources qui les affectent. Diverses hypothèses émergent de cette conceptualisation théorique. La première est que les conditions de l’organisation du travail contribuent directement aux variations de la sécrétion de cortisol salivaire. La deuxième est que les conditions de l’organisation du travail contribuent directement à l’épuisement professionnel. La troisième est que la sécrétion de cortisol salivaire médiatise la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. La quatrième est que la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire est modérée par les traits de personnalité. La cinquième est que la relation entre les conditions de l’organisation du travail, la sécrétion de cortisol salivaire et l’épuisement professionnel est modérée par les traits de personnalité. Des modèles de régression multiniveaux et des analyses de cheminement de causalité ont été effectués sur un échantillon de travailleurs canadiens provenant de l’étude SALVEO. Les résultats obtenus sont présentés sous forme de trois articles, soumis pour publication, lesquels constituent les chapitres 4 à 6 de cette thèse. Dans l’ensemble, le modèle intégrateur biopsychosocial proposé dans le cadre de cette thèse de doctorat permet de mieux saisir la complexité de l’épuisement professionnel qui trouve une explication biologique, organisationnelle et individuelle. Ce constat permet d’offrir une compréhension élargie et multiniveaux et assure l’avancement des connaissances sur une problématique préoccupante pour les organisations, la société ainsi que pour les travailleurs. Effectivement, la prise en compte des traits de personnalité et de la sécrétion du cortisol salivaire dans l’étude de l’épuisement professionnel assure une analyse intégrée et plus objective. Cette thèse conclue sur les implications de ces résultats pour la recherche, et sur les retombées qui en découlent pour les milieux de travail.
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The aim of this paper was to obtain evidence of the validity of the LSB-50 (de Rivera & Abuín, 2012), a screening measure of psychopathology, in Argentinean adolescents. The sample consisted of 1002 individuals (49.7% male; 50.3% female) between 12 and 18 years-old (M = 14.98; SD = 1.99). A cross-validation study and factorial invariance studies were performed in samples divided by sex and age to test if a seven-factor structure that corresponds to seven clinical scales (Hypersensitivity, Obsessive-Compulsive, Anxiety, Hostility, Somatization, Depression, and Sleep disturbance) was adequate for the LSB-50. The seven-factor structure proved to be suitable for all the subsamples. Next, the fit of the seven-factor structure was studied simultaneously? in the aforementioned subsamples through hierarchical models that imposed different constrains of equivalency?. Results indicated the invariance of the seven clinical dimensions of the LSB-50. Ordinal alphas showed good internal consistency for all the scales. Finally, the correlations with a diagnostic measure of psychopathology (PAI-A) indicated moderate convergence. It is concluded that the analyses performed provide robust evidence of construct validity for the LSB-50
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Structured abstract Purpose: To deepen, in grocery retail context, the roles of consumer perceived value and consumer satisfaction, as antecedents’ dimensions of customer loyalty intentions. Design/Methodology/approach: Also employing a short version (12-items) of the original 19-item PERVAL scale of Sweeney & Soutar (2001), a structural equation modeling approach was applied to investigate statistical properties of the indirect influence on loyalty of a reflective second order customer perceived value model. The performance of three alternative estimation methods was compared through bootstrapping techniques. Findings: Results provided i) support for the use of the short form of the PERVAL scale in measuring consumer perceived value; ii) the influence of the four highly correlated independent latent predictors on satisfaction was well summarized by a higher-order reflective specification of consumer perceived value; iii) emotional and functional dimensions were determinants for the relationship with the retailer; iv) parameter’s bias with the three methods of estimation was only significant for bootstrap small sample sizes. Research limitations:/implications: Future research is needed to explore the use of the short form of the PERVAL scale in more homogeneous groups of consumers. Originality/value: Firstly, to indirectly explain customer loyalty mediated by customer satisfaction it was adopted a recent short form of PERVAL scale and a second order reflective conceptualization of value. Secondly, three alternative estimation methods were used and compared through bootstrapping and simulation procedures.
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This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.