The only certainty in a human being’s life is death. From a mathematical point of view, it is thus much more interesting to study the time it takes for someone to die,
rather than the death itself. Survival analysis is a branch of statistics widely used in various fields, including medicine, economics, and engineering, to analyze time-to-event data. With it we can not only study deaths, but also other events of interest, e.g. machine-failures or debt-defaults.
This bachelor thesis presents a comprehensive exploration of hypothesis testing in survival analysis, focusing on various aspects and challenges associated with this field. We will get to know some popular survival models for single samples, and how they may be tested with real data. We will also learn different methods for comparing the survival probability of many populations, without having to explicitly find a fitting model for each one of them. We will develop the mathematical theory and apply it with the R programming language.
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The only certainty in a human being’s life is death. From a mathematical point of view, it is thus much more interesting to study the time it takes for someone to die,
rather than the death itself. Survival analysis is a branch of statistics widely used in various fields, including medicine, economics, and engineering, to analyze time-to-event data. With it we can not only study deaths, but also other events of interest, e.g. machine-failures or debt-defaults.
This bachelor thesis presents a...
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