Competing risks occur often in survival analysis. In present work, we study different ap- proaches to modeling competing risks data and use examples to illustrate the most impor- tant results. In the competing risks setting it is often of interest to calculate the cumulative incidence of a specific event. We first study non-parametric estimation and then present three approaches to regression modeling. We use simple numerical example to demonstrate the use of non-parametric methods and perform analysis of real data from Stanford Heart Transplant Program to illustrate and compare the chosen regression models.

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. Johannesburg, December 2014. / Industrial units cannot operate without failure forever. When the operation of a unit deviates from industrial standards, it is considered to have failed. The time from the moment a unit enters service until it fails is its lifetime. Within reliability and often in life data analysis in general, lifetime is the event of interest. For highly reliable units, accelerated life testing is required to obtain lifetime data quickly. Accelerated tests where failure is not instantaneous, but the end point of an underlying degradation process are considered. Failure during testing occurs when the performance of the unit falls to some specified threshold value such that the unit fails to meet industrial specifications though it has some residual functionality (degraded failure) or decreases to a critical failure level so that the unit cannot perform its function to any degree (critical failure). This problem formulation satisfies the random signs property, a notable competing risks formulation originally developed in maintenance studies but extended to accelerated testing here. Since degraded and critical failures are linked through the degradation process, the open problem of modelling dependent competing risks is discussed. A copula model is assumed and expert opinion is used to estimate the copula. Observed occurrences of degraded and critical failure times are interpreted as times when the degradation process first crosses failure thresholds and are therefore postulated to be distributed as inverse Gaussian. Based on the estimated copula, a use-level unit lifetime distribution is extrapolated from test data. Reliability metrics from the extrapolated use-level unit lifetime distribution are found to differ slightly with respect to different degrees of stochastic dependence between the risks. Consequently, a degree of dependence between the risks that is believed to be realistic to admit is considered an important factor when estimating the use-level unit lifetime distribution from test data. Keywords: Lifetime; Accelerated testing; Competing risks; Copula; First passage time.

Currently, there are an estimated 2.8 million breast cancer survivors in the United States. Due to modern screening practices and raised awareness, the majority of these cases will be diagnosed in the early stages of disease where highly effective treatment options are available, leading a large proportion of these patients to fail from causes other than breast cancer. The primary cause of death in the United States today is cardiovascular disease, which can be delayed or prevented with interventions such as lifestyle modifications or medications. In order to identify individuals who may be at high risk for a cardiovascular event or cardiovascular mortality, a number of prognostic models have been developed. The majority of these models were developed on populations free of comorbid conditions, utilizing statistical methods that did not account for the competing risks of death from other causes, therefore it is unclear whether they will be generalizable to a cancer population remaining at an increased risk of death from cancer and other causes. Consequently, the purpose of this work is multi-fold. We will first summarize the major statistical methods available for analyzing competing risk data and include a simulation study comparing them. This will be used to inform the interpretation of the real data analysis, which will be conducted on a large, contemporary cohort of breast cancer survivors. For these women, we will categorize the major causes of death, hypothesizing that it will include cardiovascular failure. Next, we will evaluate the existing cardiovascular disease risk models in our population of cancer survivors, and then propose a new model to simultaneously predict a survivor's risk of death due to her breast cancer or due to cardiovascular disease, while accounting for additional competing causes of death. Lastly, model predicted outcomes will be calculated for the cohort, and evaluation methods will be applied to determine the clinical utility of such a model.

The main goal of the Master's Thesis is to create one year marketing plan for the Müller for year 2012, which will be in accordance with actual market position and development of the Müller company. The Master's Thesis combines theoretical and practical approach and offers a comprehensive look at the issue of marketing plan. The first part deals with the situation analysis, including internal data, research data from research agency AC Nielsen and Porter's model of competing forces. The output of the situation analysis is the evaluation of opportunities and threats, strengths and weaknesses of the company, under which the marketing goals were proposed. Regarding the marketing goals a new strategies of marketing mix were suggested. The proposal of individual activity and their timing is illustrated in the chart of the action plan. The last part summarizes the systems of measurement and controls Design of individual activities and their timing is contained in the Action Plan. At the end are summarized measurement systems and controls.

In this thesis, the competing and shifting hegemonic discourses in Turkey-EU relations in the period between 1999 Helsinki European Council and 3 October 2005 are discussed in the framework of neo-Gramscian perspectives. In this study, initially the classic theories of European integration are analyzed and on the basis of the argument that the classic theories of European integration exhausted their potentials in explaining the European integration process, the neo-Gramscian perspectives are presented as an alternative theoretical framework. Deriving from the wavering character of Turkey-EU relations, the turning points in the related time period are defined and competing and shifting hegemonic discourses for both sides are discussed. The main argument of this thesis is that, since the very beginning of Turkey-EU relations, it has a wavering character and these relations are reproduced through the redefinition of competing and shifting hegemonic discourses with the active contribution of social actors in the related time period.

Multi-state models are often used to evaluate the effect of death as a competing event to the development of dementia in a longitudinal study of the cognitive status of elderly subjects. In this dissertation, both multi-state Markov model and semi-Markov model are used to characterize the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient, cognitive states and death as a competing risk. Firstly, a multi-state Markov model with three transient states: intact cognition, mild cognitive impairment (M.C.I.) and global impairment (G.I.) and one absorbing state: dementia is used to model the cognitive panel data. A Weibull model and a Cox proportional hazards (Cox PH) model are used to fit the time to death based on age at entry and the APOE4 status. A shared random effect correlates this survival time with the transition model. Secondly, we further apply a Semi-Markov process in which we assume that the wait- ing times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for the likelihood based estimation. At the end of this dissertation we extend a non-parametric “local EM algorithm” to obtain a smooth estimator of the cause-specific hazard function (CSH) in the presence of competing risk. All the proposed methods are justified by simulation studies and applications to the Nun Study data, a longitudinal study of late life cognition in a cohort of 461 subjects.

Aalen’s additive hazards model has gained increasing attention in recently years because it model all covariate effects as time-varying. In this thesis, our goal is to explore the application of Aalen’s model in assessing treatment effect at a given time point with varying covariate effects. First, based on Aalen’s model, we utilize the direct adjustment method to obtain the adjusted survival of a treatment and comparing two direct adjusted survivals, with univariate survival data. Second, we focus on application of Aalen’s model in the setting of competing risks data, to assess treatment effect on a particular type of failure. The direct adjusted cumulative incidence curve is introduced. We further construct the confidence interval of the difference between two direct adjusted cumulative incidences, to compare two treatments on one risk.

Background: Prostate cancer is the most common cancer in Sweden with around 10,000 new cases every year. Kidney and bladder cancer are less common with 1,000 and 2,000 new cases annually, respectively. The incidence of these cancer sites is higher in developed, than in developing countries, suggesting an association between lifestyle and cancer risk. The aims of this thesis were to investigate body mass index (BMI), blood pressure, and blood levels of glucose, total cholesterol, and triglycerides as risk factors for prostate, kidney, and bladder cancer. Furthermore, we aimed at assess probabilities of prostate cancer and competing events, all-cause death, for men with normal and high levels of metabolic factors. Material and methods: This thesis was conducted within the Metabolic Syndrome and Cancer project (Me-Can), a pooled cohort study with data from 578,700 participants from Norway, Sweden, and Austria. Data from metabolic factors were prospectively collected at health examinations and linked to the Cancer and Cause of Death registers in each country.  Results: High levels of metabolic factors were not associated with increased risk of prostate cancer, but high levels of BMI and blood pressure were associated with risk of prostate cancer death. The probability of prostate cancer was higher for men with normal levels of metabolic factors compared to men with high levels, but the probability of all-cause death, was higher for men with high levels than for those with normal levels. For both men and women, high levels of metabolic factors were associated with increased risk of kidney cancer (renal cell carcinoma). Furthermore, blood pressure for men and BMI for women were found as independent risk factors of kidney cancer. High blood pressure was associated with an increased risk of bladder cancer for men. Conclusions: High levels of metabolic factors were associated to risk of kidney and bladder cancer and to death from kidney, bladder, and prostate cancer. Compared to men with normal levels, men with high levels of metabolic factors had a decreased probability of prostate cancer but an increased probability of all-cause death. / <p>Ytterligare forskningsfinansiärer: World Cancer Research Fund (2007/09) och Wereld Kanker Onderzoek Fonds (R2010/247)</p> / Me-Can

The research on multi-state Markov transition model is motivated by the nature of the longitudinal data from the Nun Study (Snowdon, 1997), and similar information on the BRAiNS cohort (Salazar, 2004). Our goal is to develop a flexible methodology for handling the categorical longitudinal responses and competing risks time-to-event that characterizes the features of the data for research on dementia. To do so, we treat the survival from death as a continuous variable rather than defining death as a competing absorbing state to dementia. We assume that within each subject the survival component and the Markov process are linked by a shared latent random effect, and moreover, these two pieces are conditionally independent given the random effect and their corresponding predictor variables. The problem of the dependence among observations made on the same subject (repeated measurements) is addressed by assuming a first order Markovian dependence structure. A closed-form expression for the individual and thus overall conditional marginal likelihood function is derived, which we can evaluate numerically to produce the maximum likelihood estimates for the unknown parameters. This method can be implemented using standard statistical software such as SAS Proc Nlmixed©. We present the results of simulation studies designed to show how the model’s ability to accurately estimate the parameters can be affected by the distributional form of the survival term. Then we focus on addressing the problem by accommodating the residual life time of the subject’s confounding in the nonhomogeneous chain. The convergence status of the chain is examined and the formulation of the absorption statistics is derived. We propose using the Delta method to estimate the variance terms for construction of confidence intervals. The results are illustrated with applications to the Nun Study data in details.

The aim of this research is to investigate the relationship between organizational and national culture and the use and effectiveness of systems development methodologies. Various different aspects of both culture and systems development methodologies are analysed. The first aspect studied is the state of systems development methodology use in South Africa. The results indicate that 74% of the organizations that participated in this study use a systems development methodology. Relationships between horizontal use of systems development methodologies and the success of the IS system and the success of the development process are also found. This relationship shows that when the systems development methodology knowledge is used in a bigger proportion of projects and by a bigger proportion of people, then both the development process and the IS system will be more successful. A relationship is also found that exists between organizational culture and system development methodologies. Organizations with a more hierarchical culture have been using SDMs longer than other organizational cultures. Relationships between national culture and systems development methodologies are also studied. The results show that when people prefer to work in a group (low individualism), the systems development methodology knowledge will be used more horizontally in the organization. The results also show relationships between the success of the IS system, the success of development process and the national and organizational cultures. When managers involve people at lower levels in the organizations in the decision making process, the developed IS system is more successful. The results show that organizations with a more developmental culture will have a more successful development system. The more an organization have a rational culture the more successful the IS system is perceived to be. / Thesis (MSc (Computer Science))--North-West University, Potchefstroom Campus, 2012.