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Full-Text Articles in Biostatistics
Two Step Parsimonious Variable Selection For Right Censored Continuous Survival Time Models, Anju Menon
Two Step Parsimonious Variable Selection For Right Censored Continuous Survival Time Models, Anju Menon
Legacy Theses & Dissertations (2009 - 2024)
Variable selection is fundamental in any kind of statistical modeling. There has been ex- tensive research by different authors on methods of variable selection from linear regression models to more complex non-linear applications. Modeling survival data especially poses challenges because of a more complicated data structure as the time variable T is usually subject to censoring. This thesis presents a two step objective approach to choose between several candidate models based on the the ability of the model to predict survival times using loss functions. Once potentially important variables are selected using a screening method called Iterative Sure Independence Screening(ISIS) …
Developing A Weibull Model Extension To Estimate Cancer Latency Times, Diana L. Nadler
Developing A Weibull Model Extension To Estimate Cancer Latency Times, Diana L. Nadler
Legacy Theses & Dissertations (2009 - 2024)
More than one-third of all Americans will be diagnosed with cancer sometime in their lives. Though their illness may be invisible now, it presents a great, and largely unexamined, opportunity to find and treat their cancers early. Early detection represents one of the most promising approaches to reduce the growing cancer burden by identifying cancer while it is localized and curable, preventing not only mortality, but also reducing morbidity and costs.