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Análise de eficiência de programas de pós-graduação em Engenharias III
(Universidade Federal de São Carlos, 2017-01-09) Costa, Naijela Janaina da; Moralles, Herick Fernando; https://lattes.cnpq.br/3603674784653923; https://lattes.cnpq.br/9395111230471879
The effectiveness of Brazil's postgraduate programs is directly linked to the country's capacity for innovation, which entails the need to diagnose the causes of low academic achievement, as well as the development of techniques and methods to evaluate and measure performance Of educational units. In this sense, the objective of this project was to analyze the efficiency of postgraduate programs in Brazilian Engineering III. Through the application of the Data Envelopment Analysis (DEA) technique, the most efficient programs were identified, and through the Tobit Regression the degree of influence of certain inputs was determined (number of professor; scholars of CNPq; Number of students) in educational performance. The results of this project can contribute to a better understanding of the dynamics and determining factors of the national academic production, in order to generate knowledge about postgraduate programs, especially courses that did not reach the production efficiency standards Required by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
Modeling based on a reparameterized Birnbaum-Saunders distribution for analysis of survival data
(Universidade Federal de São Carlos, 2017-01-09) Leão, Jeremias da Silva; Sanchez, Victor Eliseo Leiva; https://lattes.cnpq.br/8210845561629144; Tomazella, Vera Lucia Damasceno; https://lattes.cnpq.br/8870556978317000; https://lattes.cnpq.br/1079978062491227
In this thesis we propose models based on a reparameterized Birnbaum-Saunder (BS) distribution introduced by Santos-Neto et al. (2012) and Santos-Neto et al. (2014), to analyze survival data. Initially we introduce the Birnbaum-Saunders frailty model where we analyze the cases (i) with (ii) without covariates. Survival models with frailty are used when further information is nonavailable to explain the occurrence time of a medical event. The random effect is the “frailty”, which is introduced on the baseline hazard rate to control the unobservable heterogeneity of the patients. We use the maximum likelihood method to estimate the model parameters. We evaluate the performance of the estimators under different percentage of censured observations by a Monte Carlo study. Furthermore, we introduce a Birnbaum-Saunders regression frailty model where the maximum likelihood estimation of the model parameters with censored data as well as influence diagnostics for the new regression model are investigated. In the following we propose a cure rate Birnbaum-Saunders frailty model. An important advantage of this proposed model is the possibility to jointly consider the heterogeneity among patients by their frailties and the presence of a cured fraction of them. We consider likelihood-based methods to estimate the model parameters and to derive influence diagnostics for the model. In addition, we introduce a bivariate Birnbaum-Saunders distribution based on a parameterization of the Birnbaum-Saunders which has the mean as one of its parameters. We discuss the maximum likelihood estimation of the model parameters and show that these estimators can be obtained by solving non-linear equations. We then derive a regression model based on the proposed bivariate Birnbaum-Saunders distribution, which permits us to model data in their original scale. A simulation study is carried out to evaluate the performance of the maximum likelihood estimators. Finally, examples with real-data are performed to illustrate all the models proposed here.