# Empirical Bayes logistic regression

Strimenopoulou, Foteini, Brown, Philip J. (2008) Empirical Bayes logistic regression. Statistical Applications in Genetics and Molecular Biology, 7 (2). ISSN 1544-6115. (doi:10.2202/1544-6115.1359) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

 The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) Official URLhttp://dx.doi.org/10.2202/1544-6115.1359

## Abstract

We construct a diagnostic predictor for patient disease status based on a single data set of mass spectra of serum samples together with the binary case-control response. The model is logistic regression with Bernoulli log-likelihood augmented either by quadratic ridge or absolute $L_1$ penalties. For ridge penalization using the singular value decomposition we reduce the the number of variables for maximization to the rank of the design matrix. With log-likelihood loss, 10-fold cross-validatory choice is employed to specify the penalization hyperparameter. Predictive ability is judged on a set-aside subset of the data.

Item Type: Article 10.2202/1544-6115.1359 Article No 9 Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics Philip J Brown 07 Mar 2009 13:00 UTC 28 May 2019 13:43 UTC https://kar.kent.ac.uk/id/eprint/8191 (The current URI for this page, for reference purposes)