Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces

@inproceedings{Gentry2015PenalizedOR,
  title={Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces},
  author={Amanda Elswick Gentry and Colleen K. Jackson-Cook and Debra E Lyon and Kellie J. Archer},
  booktitle={Cancer informatics},
  year={2015}
}
The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated features are lacking. In this paper, we propose a method that fits an ordinal response model to predict an ordinal outcome for high-dimensional covariate spaces. Our method penalizes some covariates… CONTINUE READING
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