1000 resultados para Modelos lineares generalizados
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A modelagem conjunta de média e variância tem se mostrado particularmente relevante na obtenção de processos e produtos robustos. Nesse contexto, deseja-se minimizar a variabilidade das respostas simultaneamente com o ajuste dos fatores, tal que se obtenha a média da resposta próxima ao valor alvo. Nos últimos anos foram desenvolvidos diversos procedimentos de modelagem conjunta de média e variância, alguns envolvendo a utilização dos Modelos Lineares Generalizados (GLMs) e de projetos fatoriais fracionados. O objetivo dessa dissertação é apresentar uma revisão bibliográfica sobre projetos fatoriais fracionados e GLM, bem como apresentar as propostas de modelagem conjunta encontradas na literatura. Ao final, o trabalho enfatiza a proposta de modelagem conjunta de média e variância utilizando GLM apresentada por Lee e Nelder (1998), ilustrando-a através de um estudo de caso.
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São estabelecidas as matrizes necessárias para a realização da análise de variância de experimentos em parcelas subdivididas, com dados não-balanceados e balanceados, quando os tratamentos aplicados às parcelas e os tratamentos aplicados às subparcelas são ambos fatores quantitativos, usando a teoria de modelos lineares e de modelos lineares generalizados. Foi desenvolvido um programa computacional, na linguagem GLIM, para a realização da análise.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In the composition of this work are present two parts. The first part contains the theory used. The second part contains the two articles. The first article examines two models of the class of generalized linear models for analyzing a mixture experiment, which studied the effect of different diets consist of fat, carbohydrate, and fiber on tumor expression in mammary glands of female rats, given by the ratio mice that had tumor expression in a particular diet. Mixture experiments are characterized by having the effect of collinearity and smaller sample size. In this sense, assuming normality for the answer to be maximized or minimized may be inadequate. Given this fact, the main characteristics of logistic regression and simplex models are addressed. The models were compared by the criteria of selection of models AIC, BIC and ICOMP, simulated envelope charts for residuals of adjusted models, odds ratios graphics and their respective confidence intervals for each mixture component. It was concluded that first article that the simplex regression model showed better quality of fit and narrowest confidence intervals for odds ratio. The second article presents the model Boosted Simplex Regression, the boosting version of the simplex regression model, as an alternative to increase the precision of confidence intervals for the odds ratio for each mixture component. For this, we used the Monte Carlo method for the construction of confidence intervals. Moreover, it is presented in an innovative way the envelope simulated chart for residuals of the adjusted model via boosting algorithm. It was concluded that the Boosted Simplex Regression model was adjusted successfully and confidence intervals for the odds ratio were accurate and lightly more precise than the its maximum likelihood version.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Zootecnia - FCAV
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Pós-graduação em Enfermagem - FMB
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This is an ecological, analytical and retrospective study comprising the 645 municipalities in the State of Sao Paulo, the scope of which was to determine the relationship between socioeconomic, demographic variables and the model of care in relation to infant mortality rates in the period from 1998 to 2008. The ratio of average annual change for each indicator per stratum coverage was calculated. Infant mortality was analyzed according to the model for repeated measures over time, adjusted for the following correction variables: the city's population, proportion of Family Health Programs (PSFs) deployed, proportion of Growth Acceleration Programs (PACs) deployed, per capita GDP and SPSRI (Sao Paulo social responsibility index). The analysis was performed by generalized linear models, considering the gamma distribution. Multiple comparisons were performed with the likelihood ratio with chi-square approximate distribution, considering a significance level of 5%. There was a decrease in infant mortality over the years (p < 0.05), with no significant difference from 2004 to 2008 (p > 0.05). The proportion of PSFs deployed (p < 0.0001) and per capita GDP (p < 0.0001) were significant in the model. The decline of infant mortality in this period was influenced by the growth of per capita GDP and PSFs.
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Pós-graduação em Saúde Coletiva - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Amphibian populations worldwide have been suffering declines generated by habitat degradation, loss, fragmentation and habitat split. With habitat loss and fragmentation in the landscape comes habitat split, which is the separation between the adult anuran habitat and breeding sites, forcing individuals to move through matrix during breeding seasons. Thus, habitat split increases the chance of extinction of amphibians with aquatic larval development and acts as a filter in the selection of species having great influence on species richness and community structure. The use of functional diversity allows us to consider the identity and characteristics of each species to understand the effects of fragmentation processes. The objective of this study was to estimate the effects of habitat split, as well as habitat loss in the landscape, on amphibians functional diversity (FD) and species richness (S). We selected 26 landscapes from a database with anuran surveys of Brazilian Atlantic Forest. For each landscape we calculated DF, S and landscape metrics at multiple scales. To calculate the DF we considered traits that influenced species use and persistence in the landscape. We refined maps of forest remnants and water bodies for metrics calculation. To relate DF and S (response variables) to landscape variables (explanatory variables), we used a model selection approach, fitting generalized linear models (GLMS) and making your selection with AICc. We compared the effect of model absence and models with habitat split, habitat amount and habitat connectivity effects, as well as their interaction. The most plausible models for S were the sum and interaction between habitat split in 7.5 km scale. For anurans with terrestrial development, habitat amount was the only plausible explanatory variable, in the 5 km scale. For anurans with aquatic larvae habitat amount in larger scales and the addition of habitat amount and habitat split were plausible...
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)