Survival Analysis Techniques - Time-to-Event Modeling: Investigating survival analysis techniques for modeling time-to-event data, commonly used in healthcare and reliability engineering
Keywords:
Survival analysis, Cox proportional hazards modelAbstract
Survival analysis is a statistical method for analyzing time-to-event data, where the primary interest is the time until an event of interest occurs. This paper provides an overview of survival analysis techniques, focusing on their application in healthcare and reliability engineering. We discuss the key concepts of censoring, survival functions, hazard functions, and the Kaplan-Meier estimator. We also explore parametric and non-parametric survival models, including the Cox proportional hazards model. Additionally, we review advanced topics such as competing risks and time-dependent covariates. This paper aims to provide a comprehensive understanding of survival analysis techniques and their practical application in modeling time-to-event data.
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