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 34 for “"Competing Risks"”.
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Non-parametric competing risks with multivariate frailty models
This research focuses on two theories: (i) competing risks and (ii) random eect (frailty) models. The theory of competing risks provides a structure for inference in problems where cases are subject to several types of failure. Random eects in competing risk models consist of two underlying …
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Confidence Interval Estimation of Cumulative Incidence for Clustered Competing Risks
… outcome patients are sometimes exposed to competing events. These are risks that alter the probability of the primary outcome occurring. Traditional methods of estimating the cumulative incidence for an outcome and its associated confidence interval under competing risks do not account for …
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JOINT MODELING OF MULTIVARIATE LONGITUDINAL DATA AND COMPETING RISKS DATA
… as well as one or more time to event outcomes. A competing risks situation arises when the probability of occurrence of one event isaltered/hindered by another time to event. A classical example is different causes of death. When the missing data mechanism in the longitudinal process is …
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Joint Models for Longitudinal Analysis and Competing Risks in Survival Analysis
… 1. Linking the Cause-specific Hazards Model for competing risks analyses with a model for longitudinal ordinal measurements through a correlated random effects structure. To do this, we apply a 2009 approach by Li et al. (2009), and use this as the baseline model. 2. Developing a joint …
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Analysis of clustered competing risks with application to a multicentre clinical trial
… mutually-exclusive causes, data are said to have competing risks. For competing risks data, the Fine and Gray proportional hazards model for sub-distributions has gained popularity due to its convenience in directly assessing the effect of covariates on the cumulative incidence function. …
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The Competing Risks of Prepayment and Default on the Single-Family Mortgage Market
… become increasingly important to understand the competing risks of prepayment and default on the single-family mortgage market. This research studies the economic factors that affect the competing risks of prepayment and default in locations where the aggregate of the prepayment risk and the …
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Competing Risks Models of Farm Service Agency Guaranteed Operating and Farm Ownership Loans
<p>This thesis examines the possible outcomes (expired with no loss, settled for loss, still performing) of loans and the time to hazard events of over 19,000 guaranteed operating and farm ownership loans which were provided by the Farm Service Agency (FSA). Loans guaranteed by FSA are made by …
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Competing risks models of economic behavior : theory and applications to retirement and unemployment
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 1987.
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The analysis of limit orders using the Cox proportional hazards model with independent competing risks
… Cox proportional hazards model with independent competing risks to study the hazard rates of executed, cancelled, and partially executed limit orders submitted for Microsoft to the Island ECN for one day. The instantaneous probability of execution increases with decreases in the buy order price …
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Reliability Analysis And Optimal Maintenance Planning For Repairable Multi-Component Systems Subject To Dependent Competing Risks
… for multi-component systems with dependent competing risks under imperfect assumptions are proposed, i.e., generalized dependent latent age model and copula-based trend-renewal process model. The generalized dependent latent age model generalizes the partially perfect repair model by …
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Semiparametric Regression Under Left-Truncated and Interval-Censored Competing Risks Data and Missing Cause of Failure
… involve multiple event types, known as competing risks. The cumulative incidence function (CIF) is a particularly useful parameter as it explicitly quantifies clinical prognosis. Common issues in competing risks data analysis on the CIF include interval censoring, missing event types, …
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Deep learning survival analysis for clinical decision support in deceased donor kidney transplantation
… in order to maximize patient survival. Risks affecting patient survival post-KT must be balanced with the risks of remaining on the waitlist. These risks include mortality, graft failure, and becoming too sick to transplant. The allocation system today takes these risk into account by …
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Advances in Survival Analysis: Accurate Partial Likelihood Computation by Poisson-Binomial Distributions and Nonparametric Competing Risk Cox Model
… develops a nonparametric regression model for competing risks survival data by combining the proportional cause-specific hazards framework with a smoothing spline ANOVA approach. We establish estimation procedures and theoretical convergence rates. Simulation studies demonstrate the method's …
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Essays in financial economics
… financial phenomena using semi-parametric competing risks models. The first essay analyzes the determinants of corporate defaults and mergers. The second essay investigates how sell-side analysts make recommendation revisions facing various incentives at different points in time. The first …
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Bridging the Gap: Selected Problems in Model Specification, Estimation, and Optimal Design from Reliability and Lifetime Data Analysis
… component. Incorporating this information into a competing risks model can greatly improve the accuracy of lifetime prediction. A generalized competing risks model is proposed and simulation is used to assess its performance. In Chapter 3, optimal and compromise test plans are proposed for …
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Essays in Econometrics
… missing data, and one on survival analysis with competing risks data. The first chapter considers estimation of moment condition models when some data are missing. The inverse probability tilting (IPT) estimator of Graham et al. [2] re-weights fully observed data to account appropriately for …
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EVALUATION, DEVELOPMENT, AND EXTENSION OF FLEXIBLE PARAMETRIC MODELS FOR THE DISTRIBUTIONAL ANALYSIS OF CENSORED AND NON-CENSORED DATA: A FRAMEWORK FOR MODELING AND COMMUNICATING THE FULL DISTRIBUTION OF HEALTH OUTCOMES.
… for the Cumulative Incidence Function (CIF) in competing risks settings. • New Estimators: The thesis introduces an imputation-based Piece-wise Exponential model for the direct estimation of the sub-distribution hazard. • New Measures: To improve risk communication, two novel estimands are …
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Causal Inference with Survival Outcomes via Orthogonal Statistical Learning
… treatment effects for both survival outcomes and competing risk outcomes. Our approach combines importance sampling, semiparametric theory, and Neyman orthogonality to resolve both model misspecification and lack of covariate overlap between treatment arms in observational studies with censored …
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Nonparametric Predictive Inference for Multiple Comparisons
… of an experiment, progressive censoring and competing risks. Several selection events of interest are considered including selecting the best group, the subset of best groups, and the subset including the best group. The proposed methods use lower and upper probabilities for some events of …
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Time-to-Event Prediction Using Deep Learning Models: Application to GPU Failure Data
… we introduce a deep learning model for competing risks. We develop a custom loss function for competing risks that incorporates survival theory and is specifically adapted for time prediction. We compare this model to other machine learning approaches and benchmark it against a …
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