Colloquium Talk

Friday, March 24 at 3:15pm

St. Mary's Hall, 326 3700 Reservoir Road, N.W., Washington


Department of Mathematics & Statistics

High-Dimensional Inference of Ordinal Data with Medical Applications

Feiran Jiao

Office of Biostatistics, Center of Drug Evaluation and Research, U.S. Food and Drug Administration

Friday, March 24th, 2017 @ 3:15pm

St. Mary’s Hall 326



In this work, we develop new statistical methods for variable selection in a high-dimensional cumulative link regression model with an ordinal response. Our study is partly motivated by the needs for exploring the association structure between disease phenotype and high-dimensional medical covariates. We proposed a penalized maximum likelihood approach with a composite bridge penalty to solve the bi-level selection problem in a cumulative link model. A minorization-maximization (MM) algorithm was developed for implementing the proposed method, which is specific to each of the 4 link functions, namely, probit, logistic, Cauchy and complementary loglog links. The proposed approach is shown to enjoy a number of desirable theoretical properties including bi-level selection consistency and oracle properties, under suitable regularity conditions. Simulations demonstrate that the proposed method enjoys good empirical performance. We illustrated the proposed methods with a real medical application.


Event Type

Academic Events


Georgetown College, Mathematics and Statistics

Event Contact Name

Nate Strawn

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