Today, many financial institutions extending credit rely on automated credit scorecard decision engines to drive credit strategies that are used to allocate (application scoring) and manage (behavioural scoring) credit limits. The accuracy and predictive power of these models are meticulously monitored, to ensure that they deliver the required separation between good (non-delinquent) accounts and bad (delinquent) accounts. The strategies associated to the scores (champion strategies) produced using the scorecards, are monitored on a quarterly basis (minimum), ensuring that the limit allocated to a customer, with its associated risk, is still providing the lender with the best returns on their appetite for risk. The strategy monitoring opportunity should be used to identify possible clusters of customers that are not producing the optimal returns for the lender. The identified existing strategy (champion) that does not return the desired output is challenged with an alternative strategy that may or may not result in better results. These clusters should have a relatively low credit risk ranking, be credit hungry, and have the capacity to service the debt. This research project focuses on the management of (behavioural) strategies that manage the ongoing limit increases provided to current account holders. Utilising a combination of the behavioural scores and credit turnover, an optimal recommended or confidential limit is calculated for the customer. Once the new limits are calculated, a sample is randomly selected from the cluster of customers and tested in the operational environment. With the implementation of the challenger, strategy should ensure that the intended change on the customer's limit is well received by the customers. Measures that can be used are risk, response, retention, and revenue. The champion and challenger strategies are monitored over a period until a victor (if there is one) can be identified. It is expected that the challenger strategy should have a minimal impact on the customers affected by the experiment and that the bank should not experience greater credit risk from the increased limits. The profit from the challenger should increase the interest revenue earned from the increased limit. Once it has been established through monitoring whether the champion or the challenger strategy has won, the winning strategy is rolled-out to the rest of the customers from the champion population. / Thesis (Ph.D. (Operational Research))--North-West University, Vaal Triangle Campus, 2009.

Today, many financial institutions extending credit rely on automated credit scorecard decision engines to drive credit strategies that are used to allocate (application scoring) and manage (behavioural scoring) credit limits. The accuracy and predictive power of these models are meticulously monitored, to ensure that they deliver the required separation between good (non-delinquent) accounts and bad (delinquent) accounts. The strategies associated to the scores (champion strategies) produced using the scorecards, are monitored on a quarterly basis (minimum), ensuring that the limit allocated to a customer, with its associated risk, is still providing the lender with the best returns on their appetite for risk. The strategy monitoring opportunity should be used to identify possible clusters of customers that are not producing the optimal returns for the lender. The identified existing strategy (champion) that does not return the desired output is challenged with an alternative strategy that may or may not result in better results. These clusters should have a relatively low credit risk ranking, be credit hungry, and have the capacity to service the debt. This research project focuses on the management of (behavioural) strategies that manage the ongoing limit increases provided to current account holders. Utilising a combination of the behavioural scores and credit turnover, an optimal recommended or confidential limit is calculated for the customer. Once the new limits are calculated, a sample is randomly selected from the cluster of customers and tested in the operational environment. With the implementation of the challenger, strategy should ensure that the intended change on the customer's limit is well received by the customers. Measures that can be used are risk, response, retention, and revenue. The champion and challenger strategies are monitored over a period until a victor (if there is one) can be identified. It is expected that the challenger strategy should have a minimal impact on the customers affected by the experiment and that the bank should not experience greater credit risk from the increased limits. The profit from the challenger should increase the interest revenue earned from the increased limit. Once it has been established through monitoring whether the champion or the challenger strategy has won, the winning strategy is rolled-out to the rest of the customers from the champion population. / Thesis (Ph.D. (Operational Research))--North-West University, Vaal Triangle Campus, 2009.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 438-442).

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 257-261).

A quantidade de novos casos de câncer, o número de mortes causadas por ele e a quantidade de pessoas convivendo com a doença (cinco anos após o diagnóstico) têm crescido em todo o mundo. Em função disso, analisar dados de pacientes com câncer torna-se uma ferramenta necessária para avaliar os programas de tratamento e monitorar o progresso das iniciativas de controle da doença. No que tange a análise, a mortalidade é um dos parâmetros utilizados para avaliar os resultados dessa área e as metodologias tradicionalmente utilizadas compreendem o método de Kaplan-Meier e o modelo de Cox. Ambos, porém, desprezam que um paciente com câncer pode vir a óbito por um câncer diferente do primeiro diagnosticado ou, até mesmo, por causas não relacionadas à doença. Portanto, propomos a utilização e entendimento de métodos de análise de sobrevivência que consideram eventos competitivos a fim avaliar incidências, letalidades e fatores associados ao óbito de pacientes com câncer primário atendidos no Hospital de Clínicas de Porto Alegre entre 2002 e 2009. Os resultados obtidos permitiram um melhor conhecimento dos tipos de cânceres com maiores incidências (pele (1.920 casos), próstata (1.080 casos), brônquios e pulmões (950 casos), mama (893 casos), sistema hematopoiético e reticuloendotelial (654 casos), cólon (573 casos), esôfago (497 casos), estômago (422 casos), neoplasia maligna secundária e não especificada dos gânglios linfáticos (360 casos) e colo do útero (328 casos)) e letalidades (pâncreas (145 óbitos; 57,1%), brônquios e pulmões (527 óbitos; 55,5%) e esôfago (262 óbitos, 52,7%)), considerando os eventos competitivos. Em função das vantagens do método, recomenda-se aos pesquisadores que não desprezem, em seus estudos, situações com eventos competitivos, uma vez que há softwares e diversos materiais disponíveis que auxiliam e facilitam sua aplicação. / The amount of new cancer cases, the number of deaths caused by it, and the number of people living with the disease (five years after the diagnosis) have grown around the world. Due that, analyzing cancer patient’s data becomes a necessary tool for evaluating treatment programs and monitor the progress of the disease control initiatives. Regarding the analysis, mortality is one of the parameters used to evaluate the results of this area and the methodologies traditionally used include the Kaplan-Meier and Cox model. However, these methodologies do not consider the fact that the death of a cancer patient can be caused by a different cancer diagnosed or even by causes unrelated to the disease. Therefore, we propose the use and understanding of survival analysis methods that consider competing events in order to assess incidence, lethality and factors associated with death in patients with primary cancer attended at Hospital de Clínicas de Porto Alegre from 2002 to 2009. The results allowed a better understanding of the types of cancers with higher incidence (skin (1,920 cases), prostate (1,080 cases), bronchi and lungs (950 cases), breast (893 cases), hematopoietic and reticuloendothelial system (654 cases), colon (573 cases), esophagus (497 cases), stomach (422 cases), second malignancy and not specified lymph nodes (360 cases) and cervix (328 cases)) and lethality (pancreas (145 deaths; 57.1%), bronchi and lungs (527 deaths; 55.1%) and esophagus (262 deaths; 52.7%)), considering the competing events. In addition, we also evaluated how gender and age contribute to the risk of death from some cancers: women has bigger risk of death for esophageal cancer, while age was associated with the risk of death for prostate cancer. This study allowed characterizing the profile of cancers attended by the hospital by considering the competing events into the estimates methods. Due the advantages of the method, we recommend to researchers do not despise, in their studies, situations with competing events, since there are many softwares and materials available to help and facilitate its implementation.

A quantidade de novos casos de câncer, o número de mortes causadas por ele e a quantidade de pessoas convivendo com a doença (cinco anos após o diagnóstico) têm crescido em todo o mundo. Em função disso, analisar dados de pacientes com câncer torna-se uma ferramenta necessária para avaliar os programas de tratamento e monitorar o progresso das iniciativas de controle da doença. No que tange a análise, a mortalidade é um dos parâmetros utilizados para avaliar os resultados dessa área e as metodologias tradicionalmente utilizadas compreendem o método de Kaplan-Meier e o modelo de Cox. Ambos, porém, desprezam que um paciente com câncer pode vir a óbito por um câncer diferente do primeiro diagnosticado ou, até mesmo, por causas não relacionadas à doença. Portanto, propomos a utilização e entendimento de métodos de análise de sobrevivência que consideram eventos competitivos a fim avaliar incidências, letalidades e fatores associados ao óbito de pacientes com câncer primário atendidos no Hospital de Clínicas de Porto Alegre entre 2002 e 2009. Os resultados obtidos permitiram um melhor conhecimento dos tipos de cânceres com maiores incidências (pele (1.920 casos), próstata (1.080 casos), brônquios e pulmões (950 casos), mama (893 casos), sistema hematopoiético e reticuloendotelial (654 casos), cólon (573 casos), esôfago (497 casos), estômago (422 casos), neoplasia maligna secundária e não especificada dos gânglios linfáticos (360 casos) e colo do útero (328 casos)) e letalidades (pâncreas (145 óbitos; 57,1%), brônquios e pulmões (527 óbitos; 55,5%) e esôfago (262 óbitos, 52,7%)), considerando os eventos competitivos. Em função das vantagens do método, recomenda-se aos pesquisadores que não desprezem, em seus estudos, situações com eventos competitivos, uma vez que há softwares e diversos materiais disponíveis que auxiliam e facilitam sua aplicação. / The amount of new cancer cases, the number of deaths caused by it, and the number of people living with the disease (five years after the diagnosis) have grown around the world. Due that, analyzing cancer patient’s data becomes a necessary tool for evaluating treatment programs and monitor the progress of the disease control initiatives. Regarding the analysis, mortality is one of the parameters used to evaluate the results of this area and the methodologies traditionally used include the Kaplan-Meier and Cox model. However, these methodologies do not consider the fact that the death of a cancer patient can be caused by a different cancer diagnosed or even by causes unrelated to the disease. Therefore, we propose the use and understanding of survival analysis methods that consider competing events in order to assess incidence, lethality and factors associated with death in patients with primary cancer attended at Hospital de Clínicas de Porto Alegre from 2002 to 2009. The results allowed a better understanding of the types of cancers with higher incidence (skin (1,920 cases), prostate (1,080 cases), bronchi and lungs (950 cases), breast (893 cases), hematopoietic and reticuloendothelial system (654 cases), colon (573 cases), esophagus (497 cases), stomach (422 cases), second malignancy and not specified lymph nodes (360 cases) and cervix (328 cases)) and lethality (pancreas (145 deaths; 57.1%), bronchi and lungs (527 deaths; 55.1%) and esophagus (262 deaths; 52.7%)), considering the competing events. In addition, we also evaluated how gender and age contribute to the risk of death from some cancers: women has bigger risk of death for esophageal cancer, while age was associated with the risk of death for prostate cancer. This study allowed characterizing the profile of cancers attended by the hospital by considering the competing events into the estimates methods. Due the advantages of the method, we recommend to researchers do not despise, in their studies, situations with competing events, since there are many softwares and materials available to help and facilitate its implementation.

A quantidade de novos casos de câncer, o número de mortes causadas por ele e a quantidade de pessoas convivendo com a doença (cinco anos após o diagnóstico) têm crescido em todo o mundo. Em função disso, analisar dados de pacientes com câncer torna-se uma ferramenta necessária para avaliar os programas de tratamento e monitorar o progresso das iniciativas de controle da doença. No que tange a análise, a mortalidade é um dos parâmetros utilizados para avaliar os resultados dessa área e as metodologias tradicionalmente utilizadas compreendem o método de Kaplan-Meier e o modelo de Cox. Ambos, porém, desprezam que um paciente com câncer pode vir a óbito por um câncer diferente do primeiro diagnosticado ou, até mesmo, por causas não relacionadas à doença. Portanto, propomos a utilização e entendimento de métodos de análise de sobrevivência que consideram eventos competitivos a fim avaliar incidências, letalidades e fatores associados ao óbito de pacientes com câncer primário atendidos no Hospital de Clínicas de Porto Alegre entre 2002 e 2009. Os resultados obtidos permitiram um melhor conhecimento dos tipos de cânceres com maiores incidências (pele (1.920 casos), próstata (1.080 casos), brônquios e pulmões (950 casos), mama (893 casos), sistema hematopoiético e reticuloendotelial (654 casos), cólon (573 casos), esôfago (497 casos), estômago (422 casos), neoplasia maligna secundária e não especificada dos gânglios linfáticos (360 casos) e colo do útero (328 casos)) e letalidades (pâncreas (145 óbitos; 57,1%), brônquios e pulmões (527 óbitos; 55,5%) e esôfago (262 óbitos, 52,7%)), considerando os eventos competitivos. Em função das vantagens do método, recomenda-se aos pesquisadores que não desprezem, em seus estudos, situações com eventos competitivos, uma vez que há softwares e diversos materiais disponíveis que auxiliam e facilitam sua aplicação. / The amount of new cancer cases, the number of deaths caused by it, and the number of people living with the disease (five years after the diagnosis) have grown around the world. Due that, analyzing cancer patient’s data becomes a necessary tool for evaluating treatment programs and monitor the progress of the disease control initiatives. Regarding the analysis, mortality is one of the parameters used to evaluate the results of this area and the methodologies traditionally used include the Kaplan-Meier and Cox model. However, these methodologies do not consider the fact that the death of a cancer patient can be caused by a different cancer diagnosed or even by causes unrelated to the disease. Therefore, we propose the use and understanding of survival analysis methods that consider competing events in order to assess incidence, lethality and factors associated with death in patients with primary cancer attended at Hospital de Clínicas de Porto Alegre from 2002 to 2009. The results allowed a better understanding of the types of cancers with higher incidence (skin (1,920 cases), prostate (1,080 cases), bronchi and lungs (950 cases), breast (893 cases), hematopoietic and reticuloendothelial system (654 cases), colon (573 cases), esophagus (497 cases), stomach (422 cases), second malignancy and not specified lymph nodes (360 cases) and cervix (328 cases)) and lethality (pancreas (145 deaths; 57.1%), bronchi and lungs (527 deaths; 55.1%) and esophagus (262 deaths; 52.7%)), considering the competing events. In addition, we also evaluated how gender and age contribute to the risk of death from some cancers: women has bigger risk of death for esophageal cancer, while age was associated with the risk of death for prostate cancer. This study allowed characterizing the profile of cancers attended by the hospital by considering the competing events into the estimates methods. Due the advantages of the method, we recommend to researchers do not despise, in their studies, situations with competing events, since there are many softwares and materials available to help and facilitate its implementation.

An increasing number of studies have shown an inverse association between a personal history of cancer (PHC) and dementia/Alzheimer’s disease (AD), both in those using dementia/AD as the outcome or cancer as the outcome. This is the first study to examine this potential association in Japanese Americans; and to examine family history of cancer and its association with incident dementia. Also, the association between these two diseases in the parents of participants were analyzed. The Kame Project, conducted from 1992 through 2001 in King County, Washington was a population-based, prospective cohort study of older Japanese Americans. Conversion to incident dementia was observed throughout the follow-up period and diagnosed by standard criteria in a consensus conference. A PHC did not have a significant association with the development of dementia. Differences between this study and those conducted previously showing an inverse association between cancer and dementia or AD included a lower age of the present cohort, race/ethnicity, focus on all-cause dementia vs. AD and adjustment for the competing risk of death. A family history of cancer was inversely associated with the development of dementia. There were statistically significant trends for a dose-response association between the numbers of affected relatives with cancer and risk for dementia. The findings are most likely explained by an inverse genetic association between cancer and dementia. Older Japanese Americans (the parents) with a history of cancer were nearly 2.5 times less likely to have a history of dementia than those without a cancer history.

Magister Legum - LLM / This thesis explores the factors that our courts take into account in determining what would constitute the best interests of the child in granting or refusing relocation applications. This study deals with the formulation and interpretation of the best interests standard by South African courts in relocation cases. The courts are considering reported cases to determine which issues to take into account in determining the best interests of the child, due to the fact that the Children’s Act does not have a set list of criteria. Therefore I will focus on case law in determining what factors are taken into account in order to determine what would be in the best interests of the child with regard to the relocation application. The aim is to determine whether there is any consistent principle or policy which can act as a guideline to practitioners and our courts to direct jurisprudence in this area. The objective is to determine whether the Children’s Act provides sufficient guidelines to assist the court in determining relocation disputes. Furthermore the thesis examines what the approach of our courts is and what constitutional dimensions may arise in relocation disputes. The research aims to explore whether relocation applications (and parenting roles) are disadvantaging women (primary-caregivers). The research investigates whether the courts are gender neutral and acutely sensitive to gender in relocation applications.

There has been a wealth of research conducted on the high school dropouts spanning several decades. It is estimated that compared with those who complete high school, the average high school dropout costs the economy approximately $250,000 more over his or her lifetime in terms of lower tax contributions, higher reliance on Medicaid and Medicare, higher rates of criminal activity, and higher reliance on welfare (Levin & Belfield, 2007). The nation suffers not only because of the loss in revenue but also as a result of the education level of the population. Individuals who choose to drop out of high school are less likely to be in the labor force than adults who earned a high school credential, and they fare worse in many aspects of life. In many studies on high school dropouts, an important challenge is how to determine an appropriate structural form for a statistical model to be used in making inferences and predictions. Many useful statistical modeling for survival analysis have been developed to study the competing risks frame of probability of dropping out and the probability of graduating; however, few methods exist for establishing the actual competing risks structural form of a model when the data contains two educational milestones – drop out and graduation. In this dissertation, we first utilized the data collected from the National Education Longitudinal Study (NELS: 88/2000) and proposed a discrete time competing risks hazard model and the corresponding model selection process to study the contributions of student’s academic ability, family background, school characteristics and vocational education to the probabilities of students graduating from or dropping out of high school. This model finds a way to overcome the shortcomings of the traditional models existing in the previous research. Within educational research, missing data is very common occurrence and can easily complicate the model selection problem. Handling missing data inappropriately can lead to bias and inaccurate inferences. This dissertation applies four missing data techniques to the key attributes including listwise deletion, dummy variable adjustment, mean imputation, and multiple imputation. Recommendations were offered for future endeavors and research in finding solutions to handle missing data in educational research. Finally, we outline the implementation of the proposed methodology. This research has the potential for both theoretical merit and implications for affecting educational policy. My dissertation adds to the limited body of literature of quantitative studies of the high school dropouts. A discrete time competing risks hazard model for predicting the probability of dropping out could become part of a powerful tool to identify students at risk of dropping out.