Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 85 for “"survival data"”.
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Hierarchical modelling of multivariate survival data
… as a means of modelling multivariate survival times. The model structure follows Clayton (1978), Hougaard (1986b), and Oakes (1986, 1989). Both approximate Bayesian and maximum likelihood estimation in these models is investigated via simulation. Predicting a component of a response …
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Joint models for longitudinal and survival data
… Joint models for longitudinal and time-to-event data can be used to estimate the association between the characteristics of the longitudinal measures over time and survival time. We developed a maximum-likelihood method to joint model multiple longitudinal biomarkers and a time-to-event outcome. …
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Semi-Parametric Likelihood Functions for Bivariate Survival Data
… applications, characterization of multivariate survival distributions is still a growing area of research. The aim of this thesis is to investigate a joint probability distribution that can be derived for modeling nonnegative related random variables. We restrict the marginals to a specified …
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Bayesian approaches for survival data in pharmaceutical research.
… Bayesian network meta-analysis models for survival data based on modeling the log-hazard rates, as opposed to hazards ratios. Expert opinion is often needed to construct priors for time-to-event data, especially in pediatric and oncology studies. For this, we propose a prior elicitation …
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Separate and Joint Analysis of Longitudinal and Survival Data
… have an effect on tumor growth or patient survival. Our project emphasizes the usage of Bayesian Hierarchical Models and Win-BUGS to jointly model the survival data and the longitudinal data—mass. The results of the joint analysis indicate that the use of ultrasound and water-soluble …
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Diagnostics for joint models for longitudinal and survival data
Joint models for longitudinal and survival data are a class of models that jointly analyse an outcome repeatedly observed over time such as a bio-marker and associated event times. These models are useful in two practical applications; firstly focusing on survival outcome whilst accounting for time …
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Bayesian Nonparametric Models and Tests for Association in Survival Data
… related topics involving censored or truncated survival data. All three topics utilize a nonparametric family of densities that are centered at a parametric family such as the Weibull, normal, or log-logistic, specifically the Polya tree prior and a novel transformed Bernstein polynomial prior. …
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Goodness-of-Fit for Length-Biased Survival Data with Right-Censoring
… subjects with a disease. When estimating the survival function from onset of disease, this sampling mechanism introduces bias, which must be accounted for. If the onset times of the disease are assumed to be coming from a stationary Poisson process, this bias, which is caused by the sampling …
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A comparison of methods for analysing interval-censored and truncated survival data
… three methods for analysing right-censored data: the Cox proportional hazards model (Cox, 1972), the Buckley-James regression model (Buckley and James, 1979) and the accelerated failure time model. These models are extended to incorporate the analysis of interval-censored and left-truncated …
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Credit Risk Modeling and Analysis Using Copula Method and Changepoint Approach to Survival Data
… to identify changepoints in Cox model of survival data. The recent 2007-2009 financial crisis has been regarded as the worst financial crisis since the Great Depression by leading economists. The securitization sector took a lot of blame for the crisis because of the connection of the …
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On Logistic Regression Approach to Survival Data and Power Divergence Statistics for Life Tables
… techniques to estimate hazard rates and survival curves from survival data. These techniques allow statisticians to use parametric regression modeling on survival data in a flexible way that provides both estimates and standard errors. In the first part of this thesis, large sample …
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Logspline Density Estimation with an Application to the Study of Survival Data of Lung Cancer Patients.
… density function <em>f</em> based on sample data is studied. Our approach is to use maximum likelihood estimation to estimate the unknown density function from a space of linear splines that have a finite number of fixed uniform knots. In the end of this thesis, the method is applied to a …
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The profile and outcomes of patients with Hepatocellular Carcinoma treated with curative intent at Groote Schuur Hospital, a Tertiary Referral Centre in South Africa
… have evaluated treatment options and subsequent survival data. Objective: To identify the clinical characteristics of patients with HCC presenting to Groote Schuur Hospital and present survival data on patients treated with curative intent. Methodology: All patients who presented with HCC from 1 …
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Semiparametric Bayesian Joint Model With Variable Selection
… obtain repeated measurements or longitudinal data that includes survival or time-to-event histories. Recently, methods for jointly modeling longitudinal and survival data have gained popularity in the statistical literature. In this dissertation, we consider the problem of variable selection …
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Variable selection in discrete survival models
… model. However, variable selection for discrete survival analysis poses many challenges due to a complicated data structure. Survival data might have unobserved heterogeneity leading to biased estimates when not taken into account. Conventional variable selection methods have stability problems. …
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A Partly Linear Model for Censored Regression Quantiles
… also be useful in exploring the distribution of survival data, typically characterized by right censoring. A method for quantile regression on censored data was developed by Portnoy (2003). The recursively reweighted Censored Regression Quantile (CRQ) estimator of Portnoy (2003), which is …
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Sample Size Calculation Based on the Semiparametric Analysis of Short-term and Long-term Hazard Ratios
We derive sample size formulae for survival data with non-proportional hazard functions under both fixed and contiguous alternatives. Sample size determination has been widely discussed in literature for studies with failure-time endpoints. Many researchers have developed methods with the …
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