: Este trabalho tem como objeto o redirecionamento na política externa (RPE) - conceituado como as mudanças mais radicais, abrangentes e rápidas em política externa. Para analisar este fenômeno, são buscadas as principais condições conjunturais que podem aumentar a chance de ocorrência deste evento. Estas condições estão relacionadas ao conceito de Janela Política, que representa o período em que é rompida a inércia política e os tomadores de decisões têm condições de iniciar um processo de RPE. Objetivo: encontrar e delimitar quais as condições conjunturais que aumentam as chances de ocorrência de um RPE. Método: são utilizadas ferramentas metodológicas qualitativas e quantitativas. No segundo capítulo, a análise é feita por meio de um modelo de sobrevivência (Cox Proportional Hazard Model) que analisa o efeito das variáveis sobre os riscos de ocorrência do evento em foco, definido como as alterações mais extremas de comportamento nas votações da Assembleia Geral das Nações Unidas. No terceiro capítulo, é desenvolvida uma análise qualitativa histórica focando especificamente nos casos mais radicais de RPE, buscando identificar padrões comuns no desencadeamento dos processos em estudo; com base nestes casos, são desenvolvidas tipologias explicativas para identificar diferentes caminhos causais que levam ao evento em tela. Resultados: foi identificado que mudanças de regime e de líder político, no âmbito doméstico, e intervenções militares de potências estrangeiras aumentam os riscos de ocorrência de RPE; adicionalmente, a alta polarização política e a mudança de regime, a crise política doméstica com envolvimento de atores internacionais, os processos de isolamento internacional com imposição de sanções econômicas e os períodos de crise econômica com questionamento do modelo econômico vigente por parte dos atores políticos podem combinadamente levar à ocorrência de RPE. Conclusões: apesar da importância do interesses de atores políticos em empreender um projeto de RPE, foi identificado que determinados eventos aumentam os riscos deste processo ocorrer. / This thesis object is the foreign policy restructuring (FPR) - conceptualized as the most radical, encompassing, and fast changes in foreign policy. To analyze this phenomenon, there will be sought the main conjuncture conditions that might enhance the chances of this event occurrence. These conditions are related to the Policy Window concept, that represents a period during which the political inertia is disrupted and decision makers have the circumstances to undertake a FPR process. Objective: find and outline the conjectural conditions and variables that increase the chances of occurrence of a FPR. Methods: it will be used qualitative and quantitative methodological tools. In the second chapter, a survival model (Cox Proportional Hazard Model) analyses the effect variables related to the Policy Window concept over the risks of happening a FPR, defined as the most extreme changes of behavior in United Nations General Assembly roll-call votes. In the third chapter, a historical qualitative analysis is undertaken focusing exclusively on the most radical cases of FPR to develop explanatory typologies in order to identify causal conjunctures and common patters that lead to the outcome. Results: we identified that regime and political leader changes, in the national context, and military interventions by foreign powers enhance the risks of FPR occurrence; additionally, high political polarization combined with regime change, political crisis with international forces involvement, processes of international isolation with economic sanctions enforcement, and economic crises with political actors questioning the current economic model might be combined, configuring causal paths to a FPR. Conclusion: despite the importance of main political actors interest in implementing a FPR process, we identified that specific conjunctures and events raise the risks of a positive outcome.

: Este trabalho tem como objeto o redirecionamento na política externa (RPE) - conceituado como as mudanças mais radicais, abrangentes e rápidas em política externa. Para analisar este fenômeno, são buscadas as principais condições conjunturais que podem aumentar a chance de ocorrência deste evento. Estas condições estão relacionadas ao conceito de Janela Política, que representa o período em que é rompida a inércia política e os tomadores de decisões têm condições de iniciar um processo de RPE. Objetivo: encontrar e delimitar quais as condições conjunturais que aumentam as chances de ocorrência de um RPE. Método: são utilizadas ferramentas metodológicas qualitativas e quantitativas. No segundo capítulo, a análise é feita por meio de um modelo de sobrevivência (Cox Proportional Hazard Model) que analisa o efeito das variáveis sobre os riscos de ocorrência do evento em foco, definido como as alterações mais extremas de comportamento nas votações da Assembleia Geral das Nações Unidas. No terceiro capítulo, é desenvolvida uma análise qualitativa histórica focando especificamente nos casos mais radicais de RPE, buscando identificar padrões comuns no desencadeamento dos processos em estudo; com base nestes casos, são desenvolvidas tipologias explicativas para identificar diferentes caminhos causais que levam ao evento em tela. Resultados: foi identificado que mudanças de regime e de líder político, no âmbito doméstico, e intervenções militares de potências estrangeiras aumentam os riscos de ocorrência de RPE; adicionalmente, a alta polarização política e a mudança de regime, a crise política doméstica com envolvimento de atores internacionais, os processos de isolamento internacional com imposição de sanções econômicas e os períodos de crise econômica com questionamento do modelo econômico vigente por parte dos atores políticos podem combinadamente levar à ocorrência de RPE. Conclusões: apesar da importância do interesses de atores políticos em empreender um projeto de RPE, foi identificado que determinados eventos aumentam os riscos deste processo ocorrer. / This thesis object is the foreign policy restructuring (FPR) - conceptualized as the most radical, encompassing, and fast changes in foreign policy. To analyze this phenomenon, there will be sought the main conjuncture conditions that might enhance the chances of this event occurrence. These conditions are related to the Policy Window concept, that represents a period during which the political inertia is disrupted and decision makers have the circumstances to undertake a FPR process. Objective: find and outline the conjectural conditions and variables that increase the chances of occurrence of a FPR. Methods: it will be used qualitative and quantitative methodological tools. In the second chapter, a survival model (Cox Proportional Hazard Model) analyses the effect variables related to the Policy Window concept over the risks of happening a FPR, defined as the most extreme changes of behavior in United Nations General Assembly roll-call votes. In the third chapter, a historical qualitative analysis is undertaken focusing exclusively on the most radical cases of FPR to develop explanatory typologies in order to identify causal conjunctures and common patters that lead to the outcome. Results: we identified that regime and political leader changes, in the national context, and military interventions by foreign powers enhance the risks of FPR occurrence; additionally, high political polarization combined with regime change, political crisis with international forces involvement, processes of international isolation with economic sanctions enforcement, and economic crises with political actors questioning the current economic model might be combined, configuring causal paths to a FPR. Conclusion: despite the importance of main political actors interest in implementing a FPR process, we identified that specific conjunctures and events raise the risks of a positive outcome.

以往重複事件分析法主要用於醫學與科學領域，近來學者逐漸將其應用至經濟、商學、社會科學等領域，本篇論文採用重複事件分析法，分析S&P 500公司股票回購的行為，回顧過去學者對股票回購之研究，我們檢視公司執行股票回購的三大原因，根據我們的實證結果發現公司可能會以股票回購作為影響公司資本結構的工具，再者亦可能用以減低剩餘資金，然而，本篇論文的實證結果較不支持訊號發射理論。 / In this study, we apply Cox proportional hazard model in recurrent event analysis, which usually used in medical and science studies, to analyze the determinants of the stock repurchase events of S&P 500 companies. We investigate three main incentives that companies conduct stock repurchase. The empirical results show that companies employ repurchase as a technique to alter capital structure. In addition, companies conduct stock repurchase to distribute excess capital. In contrast, there are little evidences to support signaling undervaluation.

In this paper, we estimate the parameters $S_0(t)$ and $ eta$ in Cox proportional hazard model when data are all interval-censored. For the application of this model, data should be either exact or right-censored, therefore we transform interval-censored data into exact data by three di®erent methods and then apply Nelson-Aalen estimate to obtain $S_0(t)$ and $ eta$. The test statistic $hat{ eta}^2I(hat{ eta})$ is not approximately distributed as $chi^2_{(1)}$ but $chi^2_{(1)}$ times a constant c.

The advancement in data acquiring technology continues to see survival data sets with many covariates. This has posed a new challenge for researchers in identifying important covariates for inference and prediction for a time-to-event response variable. In this dissertation, common Cox proportional hazards model selection techniques and a random survival forest technique were compared using five performance criteria measures. These performance measures were concordance index, integrated area under the curve, and , and R2 . To carry out this exercise, a multicentre clinical trial data set was used. A simulation study was also implemented for this comparison. To develop a Cox proportional model, a training dataset of 75% of the observations was used and the model selection techniques were implemented to select covariates. Full Cox PH models containing all covariates were also incorporated for analysis for both the clinical trial data set and simulations. The clinical trial data set showed that the full model and forward selection technique performed better with the performance metrics employed, though they do not reduce the complexity of the model as much as the Lasso technique does. The simulation studies also showed that the full model performed better than the other techniques, with the Lasso technique overpenalising the model from the simulation with the smaller data set and many covariates. AIC and BIC were less effective in computation than the rest of the variable selection techniques, but effectively reduced model complexity than their counterparts for the simulations. The integrated area under the curve was the performance metric of choice for choosing the final model for analysis on the real data set. This performance metric gave more efficient outcomes unlike the other metrics on all selection techniques. This dissertation hence showed that variable selection techniques differ according to the study design of the research as well as the performance measure used. Hence, to have a good model, it is important to not use a model selection technique in isolation. There is therefore need for further research and publish techniques that work generally well for different study designs to make the process shorter for most researchers.

Indiana University-Purdue University Indianapolis (IUPUI) / Background: Tobacco use is associated with an increased risk of developing Alzheimer's disease (AD). 14% of the incidence of AD is associated with various types of tobacco exposure. Additional real-world evidence is warranted to reveal the association between tobacco use and AD in age/gender-specific subpopulations. Method: In this thesis, the relationships between diagnoses related to tobacco use and diagnoses of AD in gender- and age-specific subgroups were investigated, using health information exchange data. The non-parametric Kaplan-Meier method was used to estimate the incidence of AD. Furthermore, the log-rank test was used to compare incidence between individuals with and without tobacco related diagnoses. In addition, we used semi-parametric Cox models to examine the association between tobacco related diagnoses and diagnoses of AD, while adjusting covariates. Results: Tobacco related diagnosis was associated with increased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 60-74 years (female hazard ratio [HR] =1.26, 95% confidence interval [CI]: 1.07 – 1.48, p-value = 0.005; and male HR =1.33, 95% CI: 1.10 - 1.62, p-value =0.004). Tobacco related diagnosis was associated with decreased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 75-100 years (female HR =0.79, 95% CI: 0.70 - 0.89, p-value =0.001; and male HR =0.90, 95% CI: 0.82 - 0.99, p-value =0.023). Conclusion: Individuals with tobacco related diagnoses were associated with an increased risk of developing AD in older adults aged 60-75 years. Among older adults aged 75-100 years, individuals with tobacco related diagnoses were associated with a decreased risk of developing AD.

Indiana University-Purdue University Indianapolis (IUPUI) / The counting process is the fundamental of many real-world problems with event data. Poisson process, used as the background intensity of Hawkes process, is the most commonly used point process. The Hawkes process, a self-exciting point process fits to temporal event data, spatial-temporal event data, and event data with covariates. We study the Hawkes process that fits to heterogeneous drug overdose data via a novel semi-parametric approach. The counting process is also related to survival data based on the fact that they both study the occurrences of events over time. We fit a Cox model to temporal event data with a large corpus that is processed into high dimensional covariates. We study the significant features that influence the intensity of events.

Introdução: As técnicas mais comumente empregadas em análise de sobrevida que utilizam dados censurados são o estimador produto limite de Kaplan-Meier (KM) e o modelo de riscos proporcionais de Cox. Estas técnicas têm como suposição que a causa da perda de seguimento seja independente do tempo de sobrevida. Objetivo: O presente estudo visa a analisar o efeito das perdas de seguimento nestas duas técnicas. Material e Métodos: O estudo foi realizado utilizando-se o banco de dados dos pacientes cadastrados no Registro Hospitalar do Hospital do Câncer de São Paulo em 1994. Foram elaborados 28 bancos de dados simulando perdas informativas e não informativas. A perda informativa foi simulada transformando os óbitos em vivos, na proporção de 5 a 50%. A perda não informativa foi simulada através do sorteio de 5 a 50% do total do banco. O estimador de Kaplan-Meier (KM) foi utilizado para estimar a sobrevida acumulada no primeiro, terceiro e quinto ano de seguimento, e o modelo de riscos proporcionais de Cox para estimar as hazard ratio (HR). Todas as estimativas obtidas no KM e as HR's foram comparadas com os resultados do banco de dados original. Resultados: Houve maior proporção de perda nos pacientes com maior escolaridade, admitidos por convênio e particular e os menos graves (estádio I ou II). Quanto maior a proporção de perda informativa, maior a diferença alcançada nas estimativas realizadas pelo KM, verificando-se que a perda de seguimento superior a 15% acarretou diferenças superiores a 20% nas estimativas da probabilidade de sobrevida. As HR's foram menos afetadas, e proporções superiores a 20% de perda de seguimento acarretaram variações de cerca de 10% nas estimativas. Quando as perdas foram não informativas não houve diferenças significativas nas estimativas pelo KM e nas HR's em relação ao banco original. Conclusões: É importante avaliar se as perdas ocorridas em estudos de coorte são informativas ou não, pois se forem podem acarretar distorções principalmente nas estimativas feitas pelo método de KM. / Introduction: The Kaplan Meier product limit estimator (KM) and the Cox proportional hazard (HR) model are the most used tools in survival analysis. These two methods have the key assumption that censoring must be independent from the survival time. Objective: To analyze the consequences of loss to follow up in these two methods. Methods: The study has utilized the data of the Cancer Registry of the patients of Hospital do Cancer in São Paulo of 1994. The informative censure was simulated transforming the death by 5 to 50% into alive. Besides 5 to 50% was spared at random simulating the non-informative censoring. The survival probability and was calculated to the first, third and fifth year of follow –up. All the estimated probabilities and HR’s were compared with the results of the original data. Results: Patients with greater scholars, lower stages and admitted by health plans or private had more losses to follow up. The maximum proportion of accepted loss to follow –up is 10% to 15% when using the KM estimator, and the HR are less affected by the loss to follow-up and one can afford having 20% of it. When the losses were non informative there were no differences between the original probabilities. Conclusions: The possibility of over or under estimated probability must be analyzed in the presence of the losses to follow- up when using the KM and HR in survival analyses.

The objective of the present study is to investigate various problems associate with breast cancer and lung cancer patients. In this study, we compare the effectiveness of breast cancer treatments using decision tree analysis and come to the conclusion that although certain treatment shows overall effectiveness over the others, physicians or doctors should discretionally give different treatment to breast cancer patients based on their characteristics. Reoccurrence time of breast caner patients who receive different treatments are compared in an overall sense, histology type is also taken into consideration. To further understand the relation between relapse time and other variables, statistical models are applied to identify the attribute variables and predict the relapse time. Of equal importance, the transition between different breast cancer stages are analyzed through Markov Chain which not only gives the transition probability between stages for specific treatment but also provide guidance on breast cancer treatment based on stating information. Sensitivity analysis is conducted on breast cancer doubling time which involves two commonly used assumptions: spherical tumor and exponential growth of tumor and the analysis reveals that variation from those assumptions could cause very different statistical behavior of breast cancer doubling time. In lung cancer study, we investigate the mortality time of lung cancer patients from several different perspectives: gender, cigarettes per day and duration of smoking. Statistical model is also used to predict the mortality time of lung cancer patients.

Introdução: As técnicas mais comumente empregadas em análise de sobrevida que utilizam dados censurados são o estimador produto limite de Kaplan-Meier (KM) e o modelo de riscos proporcionais de Cox. Estas técnicas têm como suposição que a causa da perda de seguimento seja independente do tempo de sobrevida. Objetivo: O presente estudo visa a analisar o efeito das perdas de seguimento nestas duas técnicas. Material e Métodos: O estudo foi realizado utilizando-se o banco de dados dos pacientes cadastrados no Registro Hospitalar do Hospital do Câncer de São Paulo em 1994. Foram elaborados 28 bancos de dados simulando perdas informativas e não informativas. A perda informativa foi simulada transformando os óbitos em vivos, na proporção de 5 a 50%. A perda não informativa foi simulada através do sorteio de 5 a 50% do total do banco. O estimador de Kaplan-Meier (KM) foi utilizado para estimar a sobrevida acumulada no primeiro, terceiro e quinto ano de seguimento, e o modelo de riscos proporcionais de Cox para estimar as hazard ratio (HR). Todas as estimativas obtidas no KM e as HR's foram comparadas com os resultados do banco de dados original. Resultados: Houve maior proporção de perda nos pacientes com maior escolaridade, admitidos por convênio e particular e os menos graves (estádio I ou II). Quanto maior a proporção de perda informativa, maior a diferença alcançada nas estimativas realizadas pelo KM, verificando-se que a perda de seguimento superior a 15% acarretou diferenças superiores a 20% nas estimativas da probabilidade de sobrevida. As HR's foram menos afetadas, e proporções superiores a 20% de perda de seguimento acarretaram variações de cerca de 10% nas estimativas. Quando as perdas foram não informativas não houve diferenças significativas nas estimativas pelo KM e nas HR's em relação ao banco original. Conclusões: É importante avaliar se as perdas ocorridas em estudos de coorte são informativas ou não, pois se forem podem acarretar distorções principalmente nas estimativas feitas pelo método de KM. / Introduction: The Kaplan Meier product limit estimator (KM) and the Cox proportional hazard (HR) model are the most used tools in survival analysis. These two methods have the key assumption that censoring must be independent from the survival time. Objective: To analyze the consequences of loss to follow up in these two methods. Methods: The study has utilized the data of the Cancer Registry of the patients of Hospital do Cancer in São Paulo of 1994. The informative censure was simulated transforming the death by 5 to 50% into alive. Besides 5 to 50% was spared at random simulating the non-informative censoring. The survival probability and was calculated to the first, third and fifth year of follow –up. All the estimated probabilities and HR’s were compared with the results of the original data. Results: Patients with greater scholars, lower stages and admitted by health plans or private had more losses to follow up. The maximum proportion of accepted loss to follow –up is 10% to 15% when using the KM estimator, and the HR are less affected by the loss to follow-up and one can afford having 20% of it. When the losses were non informative there were no differences between the original probabilities. Conclusions: The possibility of over or under estimated probability must be analyzed in the presence of the losses to follow- up when using the KM and HR in survival analyses.