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- W2353130973 abstract "An extension of penalized ordinal response models by Qing Zhou A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2015 Major Director: Kellie J. Archer, Ph.D., Professor, Department of Biostatistics Ordinal responses are commonly seen in medical research. Many pathological evaluations and health status outcomes are reported on an ordinal scales. Some examples of ordinal outcomes include cancer stage (I, II, III and IV), or stage of liver disease (normal liver, chronic hepatitis, cirrhosis and end of stage liver disease or hepatocellular carcinoma (HCC)). In recent years, there has been a demand to understanding the pathogenic association between ordinal clinical outcomes and molecular characteristics. Genomic charactersitics are often assayed using a high-dimensional platform where the number of interrogated sites (P ) exceeds the number of samples (n). Unfortunately, traditional ordinal response models often do not perform well when the number of parameter (P ) exceed the number of observations (n). A good solution to this problem is penalization, for example, least absolute shrinkage and selection operator (LASSO). Here, we extend a LASSO method, the generalized monotone incremental" @default.
- W2353130973 created "2016-06-24" @default.
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- W2353130973 date "2016-01-01" @default.
- W2353130973 modified "2023-09-23" @default.
- W2353130973 title "An extension of penalized ordinal response models" @default.
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- W2353130973 doi "https://doi.org/10.25772/zr9n-my67" @default.
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