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Showing 1 to 6 of 6 for “"competing risks data"”.
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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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Semiparametric Regression Under Left-Truncated and Interval-Censored Competing Risks Data and Missing Cause of Failure
… studies and clinical trials with time-to-event data frequently 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 …
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Analysis of clustered competing risks with application to a multicentre clinical trial
… fail from multiple 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 …
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Risk of Lower Extremity Amputation Revision in Patients with Peripheral Vascular Disease Adjusting for a Competing Risk of Death
… (LEA) revision and reamputation adjusting for a competing risk of death, estimate the one-year event-free mortality rates for patients with peripheral vascular disease undergoing LEA, and develop predictive models for LEA revision and reamputation adjusting for a competing risk of death. Methods: …
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Empowering RCT with Multi-site Multi-source RWD: a Statistical Learning Perspective
… the scope of inference. In contrast, real-world data (RWD), such as electronic health records (EHRs), capture broader and more representative populations but introduce challenges including bias, missing data, and the lack of randomization. Integrating these data sources effectively can enhance …
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Essays in Econometrics
… estimation in the presence of 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 …