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Academic literature on the topic 'Dados censurados'
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Journal articles on the topic "Dados censurados"
Christofaro, Cristiano, and Mônica M. D. Leão. "Tratamento de dados censurados em estudos ambientais." Química Nova 37, no. 1 (2014): 104–10. http://dx.doi.org/10.1590/s0100-40422014000100019.
Full textCardoso, Fernando Flores, Guilherme Jordão de Magalhães Rosa, Robert John Tempelman, and Roberto Augusto de Almeida Torres Junior. "Modelos hierárquicos bayesianos para estimação robusta e análise de dados censurados em melhoramento animal." Revista Brasileira de Zootecnia 38, spe (July 2009): 72–80. http://dx.doi.org/10.1590/s1516-35982009001300009.
Full textContar, Thaisa de Souza, Cesar Augusto Medeiros Destro, and Gilson Alberto Rosa Lima. "Influência de dados censurados no cálculo da concentração média das variáveis de qualidade da água demanda química de oxigênio e fosfato." Engenharia Sanitaria e Ambiental 20, no. 2 (June 2015): 191–98. http://dx.doi.org/10.1590/s1413-41522015020000121484.
Full textSabino, Claudia Vilhena Schayer, Ludmila Vieira Lage, and Katiane Cristina de Brito Almeida. "Uso de métodos estatísticos robustos na análise ambiental." Engenharia Sanitaria e Ambiental 19, spe (2014): 87–94. http://dx.doi.org/10.1590/s1413-41522014019010000588.
Full textMingote, Raquel Maia, and Heliana Ferreira da Costa. "Avaliação do método de espectrometria por cintilação em meio líquido para a medida das atividades alfa e beta total em água: aplicação a águas de abastecimento público no estado de Goiás, Brasil." Engenharia Sanitaria e Ambiental 21, no. 3 (September 2016): 569–78. http://dx.doi.org/10.1590/s1413-41522016141973.
Full textSilva, Ana Lúcia Souza da, Mário Javier Ferrua Vivanco, and Fortunato Silva de Menezes. "Resíduos generalizados de Cox-Snell na avaliação do ajuste de modelos." Ciência e Agrotecnologia 28, no. 5 (October 2004): 1196–201. http://dx.doi.org/10.1590/s1413-70542004000500030.
Full textZuñiga Maldonado, Cecilia Abigail, Manuel Darío Hernández Ripalda, and José Alfredo Jiménez García. "Comparación de técnicas de imputación para tratar respuestas censuradas en un diseño de experimentos bivariado." Nova Scientia 10, no. 20 (May 25, 2018): 190–212. http://dx.doi.org/10.21640/ns.v10i20.1288.
Full textBarbosa, Maria Tereza S., and Claudio José Struchiner. "Estimativas do número de casos de aids no Brasil, corrigidas pelo atraso de notificação." Revista Brasileira de Epidemiologia 1, no. 3 (December 1998): 234–44. http://dx.doi.org/10.1590/s1415-790x1998000300003.
Full textBuongermino de Souza, Sonia, Sophia Cornbluth Szarfarc, and José Maria Pacheco de Souza. "Anemia no primeiro ano de vida em relação ao aleitamento materno." Revista de Saúde Pública 31, no. 1 (February 1997): 15–20. http://dx.doi.org/10.1590/s0034-89101997000100004.
Full textFigueira Sobrinho, Nelson, and Dantielli Assumpção Garcia. "O Plantão do Jornal Nacional como resposta ao silenciamento bolsonarista." Revista Heterotópica 3, no. 1 (June 15, 2021): 90–115. http://dx.doi.org/10.14393/htp-v3n1-2021-59067.
Full textDissertations / Theses on the topic "Dados censurados"
Santos, Daiane de Souza. "Comparações múltiplas para dados censurados." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11072013-143209/.
Full textThe aim of this work is to study the performance of some Multiple Comparison Methods (MCMs) that adjust the p-value when the log-rank-type and Cramér-von Mises statistics are used, both nonparametric and with dependency structure. The advantage of these methods is that they control the error rates of type I and type II for each hypothesis in order to achieve high statistical power while keeping the Family Wise Error Rate (FWER) lower or equal than a given significance level. The classical Bonferroni procedure is used as well as others seen as its improvement, with special attention to certain procedures derived from Simes\' method for making inferences on individual hypothesis. It is theoretically proved that the weighted Log-Rank statistics belongs to the multivariate totally positive of order 2 (\'MTP IND. 2\') class, which is needed in order to apply Simes\' method, that guarantees control of the FWER of dependent statistics in this case. The control of the FWER when the Cramér-von Mises statistics is used is only veried by means of computational simulations. The MCMs are also analyzed by means of computational experiments with discrete and continuous data under censoring with focus on the problem of comparisons of treatment versus a control
Rasteiro, Louise Rossi. "Regressão quantílica para dados censurados." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-09072017-141021/.
Full textCensored quantile regression is an extension of quantile regression, and because it incorporates information from censored data in the modelling, and presents quite satisfactory properties, this class of models can be seen as a complementary approach to the traditional methods in Survival Analysis, with the advantage of allowing inferential conclusions to be made easily in terms of survival times rather than in terms of risk rates or as functions of survival time. Moreover, in some cases, it can also be seen as an alternative methodology to the classical models when their assumptions are violated or when modelling heterogeneity of the data. This dissertation presents three techniques for modelling censored quantile regression, which differ by assumptions and parameter estimation method. A simulation study designed with normal, Weibull and loglogistic distribution is presented to evaluate bias, standard error and mean square error. The advantages and disadvantages of each of the three techniques are then discussed and one of them is applied to a real data set from the Heart Institute of Hospital das Clínicas, University of São Paulo.
Argenton, Juliana Luz Passos 1984. "Árvore de regressão para dados censurados e correlacionados." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307181.
Full textDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: O objetivo deste trabalho é apresentar uma metodologia de árvore de regressão para dados censurados e correlacionados. O conjunto de dados analisado foi obtido a partir de uma pesquisa realizada entre Dezembro de 2005 e Janeiro de 2006, que entrevistou 119 famílias (1712 indivíduos) que vivem no pequeno vilarejo de Baependi, no Estado de Minas Gerais. São apresentadas duas metodologias com base no modelo de riscos proporcionais, a primeira desconsidera a possível correlação existente entre os indivíduos de uma mesma família e usa a primeira iteração da estimativa da verossimilhança completa nas divisões dos nós. Na segunda metodologia apresentada, a correlação entre os indivíduos de uma mesma família é incorporada no modelo de riscos proporcionais através de uma variável de fragilidade com distribuição Gama, neste caso o valor da estatística Escore é usado para escolher a melhor divisão dos nós. O objetivo da análise é avaliar as variáveis que aumentam o risco de apresentar hipertensão, diabetes tipo II e colesterol alto, que são os três principais fatores que aumentam o risco de doenças no coração. As variáveis respostas são as idades de diagnóstico desses fatores de risco. A censura é definida de acordo com a observação da idade do indivíduo no momento do diagnóstico da doença e a idade do indivíduo no momento da pesquisa. Desta forma, uma idade de diagnóstico maior que a idade no momento da pesquisa caracteriza a censura.
Abstract: The objective of this work is to present methods of regression trees for censored and correlated data. The dataset analyzed was obtained from a survey, in which 119 families (1712 individuals) living in Baependi village, in the Brazilian state of Minas Gerais, were interviewed. Two methodologies based on the proportional hazard model are presented. The first disregards the possible correlation among the individuals of the same family, using the first step of a full likelihood estimation procedure for splitting nodes. In the second methodology, the correlation among the individuals of the same family is incorporated in the proportional hazard model through a frailty variable with Gamma distribution. In this case, the value of the Score statistic is used for choosing the best splitting node. The main purpose of the analysis is to evaluate the variables that increase the risk of hypertension, type II diabetes and high cholesterol, which are the top three main factors that increase the risk of heart conditions. The response variables are the age-of-onset of these risk factors. Censoring is defined by observing the individual's age-of-onset at the moment of diagnosis and also at the moment of the survey. This way, an age-of-onset higher than the age at the moment of the survey indicates censoring.
Mestrado
Estatistica
Mestra em Estatística
Janeiro, Vanderly. "Modelagem de dados contínuos censurados, inflacionados de zeros." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-20092010-090511/.
Full textMuch equipment used to quantify substances, such as toxins in foods, is unable to measure low amounts. In cases where the substance exists, but in an amount below a small fixed value \'ksi\' , the equipment usually indicates that the substance is not present, producing values equal to zero. In cases where the quantity is between \'\'ksi\' and a known threshold value \'tau\', it detects the presence of the substance but is unable to measure the amount. When the substance exists in amounts above the threshold value ?, it is measure continuously, giving rise to a continuous random variable X whose domain can be written as the union of intervals, [ómicron, \"ksai\'), [\"ksai\', \'tau\' ] and (\'tau\', ?), This random variable commonly has an excess of zero values. In this work we propose models that can detect the probability of true zero, such as the mixture model with two components, one being degenerate at zero and the other with continuous distribution, where we considered the distributions: exponential, Weibull and gamma. Then, for each model, its characteristics were observed, procedures for estimating its parameters were proposed and its potential for adjustment by simulation methods was evaluated. Finally, the methodology was illustrated by modeling measures of contamination with aflatoxin B1, detected in grains of corn from three sub-samples of a batch of corn analyzed at the laboratory of of Mycotoxins, Department of Agribusiness, Food and Nutrition ESALQ/USP. In conclusion, in the majority of cases the simulations indicated that the proposed methods are efficient in estimating the parameters of the models, in particular for estimating the parameter ? and the expected value, E(Y). The modeling of measures of aflatoxin, in turn, showed that the proposed models are appropriate for the actual data, however the mixture model with a Weibull distribution fits the data best.
Garay, Aldo William Medina. "Modelos de regressão para dados censurados sob distribuições simétricas." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-15062014-000915/.
Full textThis work aims to present a classical and Bayesian approach to linear models with censored observations, which is a new area of research with great potential for applications. Here, we replace the conventional use of the normal distribution for the errors of a more flexible family of distributions, which deal in more appropriately with censored observations in the presence of outliers. This family is obtained through a mechanism easy to construct and has as special cases the distributions Student t, Pearson type VII, slash, contaminated normal, and obviously normal. For the case of correlated and censored responses we propose a model of robust linear regression based on Student\'s t distribution and we developed an EM type algorithm based on the first two moments of the truncated Student\'s t distribution.
Costa, Denise Reis 1985. "Estimação robusta em modelos de variáveis latentes para dados censurados." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683.
Full textTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Modelos de variáveis latentes são amplamente utilizados por psicometristas, econometristas e pesquisadores da área de ciencias sociais para modelar variáveis que não podem ser medidas diretamente, conhecidas como construtos ou efeitos aleatórios (Skrondal e Rabe-Hesketh, 2004). Na literatura, é muito comum verificar a utilização da distribuição normal para a modelagem dessas variáveis, contudo tal suposição pode ser inadequada, especialmente na presença de valores discrepantes. Preocupados com a sensibilidade das inferências sob a presença de potenciais pontos discrepantes ou com dados provenientes de distribuições com caudas pesadas, nesta tese propomos métodos de inferência robusta, utilizando a distribuição t de Student multivariada, para dois tipos de modelos de variáveis latentes: o modelo linear generalizado misto para respostas binárias (GLMM) e o modelo de análise fatorial Tobit (TCFA) para respostas contínuas e censuradas. Para a estimação dos parâmetros dos modelos estudados, um algoritmo do tipo EM foi proposto e este apresenta expressões fechadas no passo E que utiliza os dois primeiros momentos de uma distribuição multivariada t truncada. Adicionalmente apresentamos uma abordagem via análise Bayesiana e propomos medidas de diagnóstico de influência para dados censurados sob o modelo TCFA quando a suposição de normalidade é assumida. Para avaliação dos métodos propostos, foram realizados alguns estudos simulados, além da aplicação a conjuntos de dados reais.
Abstract: Latent variable models are broadly used by psychometrists, econometrists and social science researchers to model variables that cannnot be directly measured, known as constructs or random effects (Skrondal and Rabe-Hesketh, 2004). In the literature, such variables are commonly modeled with a normal distribution, but such assumption may be inadequate, especially when there are outliers. Concerned with the sensitivity of the inferences under the presence of potential outliers or data derived from heavy-tailed distributions, this thesis proposes robust inference models, using the mutivariate t-Student distribution, for two types of latent variable models: the Generalized Linear Mixed Model for correlated binary data (GLMM) and the Tobit Confirmatory Factor Analysis (TCFA) for continuous and censored data. In order to estimate the parameters of the studied models, an EM-type algorithm was proposed. This algorithm presents closed expressions on the E-step which use the two first moments of a multivariate truncated t-distribution. Moreover, we present a Bayesian approach and propose measures of influence diagnostics for censored data under the TCFA model when normality is assumed. In order to evaluate the proposed methods, simulated studies were carried out, as well as the application on real datasets.
Doutorado
Estatistica
Doutor em Estatística
Melo, Brian Alvarez Ribeiro de. "Análise Bayesiana de modelos de mistura finita com dados censurados." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-11052017-163847/.
Full textFinite mixtures are highly flexible parametric models capable of describing different data features and are widely considered in many contexts, especially in the analysis of heterogeneous data (Marin, 2005). Generally, in finite mixture models, all the components belong to the same parametric family and are only distinguished by the associated parameter vector. In this thesis, we propose a new finite mixture model, capable of handling censored observations, in which the components are the densities from the Gama, Lognormal and Weibull distributions (the GLW finite mixture). These densities are rewritten in such a way that the mean and the variance are the parameters, since the interpretation of such quantities is widespread in various areas of study. In short, we constructed the GLW model and developed its analysis under the bayesian perspective of inference considering scenarios with censorship and cure rate. This analysis includes the parameter estimation, wich is made through simulation methods, construction of hypothesis testing to evaluate covariate effects and to assess the values of the mixture weights, computatution of model adequability measures, which are used to compare different models and estimation of the predictive distribution for new observations. In a simulation study, we evaluated the feasibility of the GLW mixture to recover the original distribution of failure times using hypothesis testing and some model estimated quantities as criteria for selecting the correct distribution. The models developed were applied in the study of the follow-up time of patients with heart failure from the Heart Institute of the University of Sao Paulo Medical School. In this application, results show a better fit of mixture models, in relation to the use of only one distribution in the modeling of the failure times. Finally, we developed a package for the adjustment of the presented models in software R.
Couto, Epaminondas de Vasconcellos. "Modelo de regressão log-gama generalizado exponenciado com dados censurados." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-112500/.
Full textIn the present study, we propose a regression model using the exponentiated generalized gama (EGG) distribution for censored data, this new distribution is an extension of the generalized gama distribution. The EGG distribution (CORDEIRO et al., 2009) that has four parameters it can model survival data when the risk function is increasing, decreasing, form of U and unimodal-shaped. In this work comes to a natural expansion of the EGG distribution for censored data, is awake distribution the interest for the fact of representing a parametric family that has, as particular cases, other distributions which are broadly used in lifetime data analysis, as the generalized gama (STACY, 1962), Weibull, exponentiated Weibull (MUDHOLKAR et al., 1995, 1996), exponentiated exponential (GUPTA; KUNDU, 1999, 2001), generalized Rayleigh (KUNDU; RAKAB, 2005), among others, and it is shown useful in the discrimination among some models alternative probabilistics. Considering censored data, the maximum likelihood estimator is considered for the proposed model parameters. Another proposal of this work was to introduce a log-exponentiated generalized gamma regression model with random eect. Finally, three applications were presented to illustrate the proposed distribution.
Oyata, Victor Manuel Maehara. "Regressão para dados censurados sob mistura da distribuição gaussiana inversa com sua reciproca complementar." [s.n.], 1994. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307308.
Full textDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Ciencia da Computação
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Resumo: Não informado
Abstract: Not informed
Mestrado
Mestre em Estatística
Massuia, Monique Bettio 1989. "Modelos para dados censurados sob a classe de distribuições misturas de escala skew-normal." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306680.
Full textDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica
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Resumo: Este trabalho tem como objetivo principal apresentar os modelos de regressão lineares com respostas censuradas sob a classe de distribuições de mistura de escala skew-normal (SMSN), visando generalizar o clássico modelo Tobit ao oferecer alternativas mais robustas à distribuição Normal. Um estudo de inferência clássico é desenvolvido para os modelos em questão sob dois casos especiais desta família de distribuições, a Normal e a t de Student, utilizando o algoritmo EM para obter as estimativas de máxima verossimilhança dos parâmetros dos modelos e desenvolvendo métodos de diagnóstico de influência global e local com base na metodologia proposta por Cook (1986) e Poom & Poon (1999). Sob o enfoque Bayesiano, o modelo de regressão para respostas censuradas é estudado sob alguns casos especiais da classe SMSN, como a Normal, a t de Student, a skew-Normal, a skew-t e a skew-Slash. Neste caso, o amostrador de Gibbs é a principal ferramenta utilizada para a inferência sobre os parâmetros do modelo. Apresentamos também alguns estudos de simulação para avaliar a metodologia desenvolvida que, por fim, é aplicada em dois conjuntos de dados reais. Os pacotes SMNCensReg, CensRegMod e BayesCR para o software R dão suporte computacional aos desenvolvimentos deste trabalho
Abstract: This work aims to present the linear regression model with censored response variable under the class of scale mixture of skew-normal distributions (SMSN), generalizing the well known Tobit model as providing a more robust alternative to the normal distribution. A study based on classic inference is developed to investigate these censored models under two special cases of this family of distributions, Normal and t-Student, using the EM algorithm for obtaining maximum likelihood estimates and developing methods of diagnostic based on global and local influence as suggested by Cook (1986) and Poom & Poon (1999). Under a Bayesian approach, the censored regression model was studied under some special cases of SMSN class, such as Normal, t-Student, skew-Normal, skew-t and skew-Slash. In these cases, the Gibbs sampler was the main tool used to make inference about the model parameters. We also present some simulation studies for evaluating the developed methodologies that, finally, are applied on two real data sets. The packages SMNCensReg, CensRegMod and BayesCR implemented for the software R give computational support to this work
Mestrado
Estatistica
Mestra em Estatística