949 resultados para Multivariate Lifetime Data


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We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

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In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

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This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

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In survival analysis, the response is usually the time until the occurrence of an event of interest, called failure time. The main characteristic of survival data is the presence of censoring which is a partial observation of response. Associated with this information, some models occupy an important position by properly fit several practical situations, among which we can mention the Weibull model. Marshall-Olkin extended form distributions other a basic generalization that enables greater exibility in adjusting lifetime data. This paper presents a simulation study that compares the gradient test and the likelihood ratio test using the Marshall-Olkin extended form Weibull distribution. As a result, there is only a small advantage for the likelihood ratio test

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Matematica Aplicada e Computacional - FCT

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Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

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Pós-graduação em Ciência e Tecnologia Animal - FEIS

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In this paper we introduce an extension of the Lindley distribution which offers a more flexible model for lifetime data. Several statistical properties of the distribution are explored, such as the density, (reversed) failure rate, (reversed) mean residual lifetime, moments, order statistics, Bonferroni and Lorenz curves. Estimation using the maximum likelihood and inference of a random sample from the distribution are investigated. A real data application illustrates the performance of the distribution. (C) 2011 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

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In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

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Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.

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In many applications of lifetime data analysis, it is important to perform inferences about the change-point of the hazard function. The change-point could be a maximum for unimodal hazard functions or a minimum for bathtub forms of hazard functions and is usually of great interest in medical or industrial applications. For lifetime distributions where this change-point of the hazard function can be analytically calculated, its maximum likelihood estimator is easily obtained from the invariance properties of the maximum likelihood estimators. From the asymptotical normality of the maximum likelihood estimators, confidence intervals can also be obtained. Considering the exponentiated Weibull distribution for the lifetime data, we have different forms for the hazard function: constant, increasing, unimodal, decreasing or bathtub forms. This model gives great flexibility of fit, but we do not have analytic expressions for the change-point of the hazard function. In this way, we consider the use of Markov Chain Monte Carlo methods to get posterior summaries for the change-point of the hazard function considering the exponentiated Weibull distribution.

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In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

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Corporate Social Responsibility (CSR) addresses the responsibility of companies for their impacts on society. The concept of strategic CSR is becoming increasingly mainstreamed in the forest industry, but there is, however, little consensus on the definition and implementation of CSR. The objective of this research is to build knowledge on the characteristics of CSR and to provide insights on the emerging trend to increase the credibility and legitimacy of CSR through standardization. The study explores how the sustainability managers of European and North American forest companies perceive CSR and the recently released ISO 26000 guidance standard on social responsibility. The conclusions were drawn from an analysis of two data sets; multivariate survey data based on one subset of 30 European and 13 North American responses, and data obtained through in-depth interviewing of 10 sustainability managers that volunteered for an hour long phone discussion about social responsibility practices at their company. The analysis concluded that there are no major differences in the characteristics of cross-Atlantic CSR. Hence, the results were consistent with previous research that suggests that CSR is a case- and company-specific concept. Regarding the components of CSR, environmental issues and organizational governance were key priorities in both regions. Consumer issues, human rights, and financial issues were among the least addressed categories. The study reveals that there are varying perceptions on the ISO 26000 guidance standard, both positive and negative. Moreover, sustainability managers of European and North American forest companies are still uncertain regarding the applicability of the ISO 26000 guidance standard to the forest industry. This study is among the first to provide a preliminary review of the practical implications of the ISO 26000 standard in the forest sector. The results may be utilized by sustainability managers interested in the best practices on CSR, and also by a variety of forest industrial stakeholders interested in the practical outcomes of the long-lasting CSR debate.