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Advances in Urology
Volume 2012 (2012), Article ID 276501, 8 pages
http://dx.doi.org/10.1155/2012/276501
Research Article

Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors

1Department of Mathematics and Statistics, Oakland University, 2200 N. Squirrel Road, Rochester, MI 48309, USA
2Department of Computer Science and Engineering, Oakland University, Rochester, MI 48309, USA
3Beaumont Health System, William Beaumont Hospital, Royal Oak, MI 48073, USA
4Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA

Received 19 July 2012; Revised 25 September 2012; Accepted 25 September 2012

Academic Editor: Miroslav L. Djordjevic

Copyright © 2012 Theophilus O. Ogunyemi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Theophilus O. Ogunyemi, Mohammad-Reza Siadat, Suzan Arslanturk, Kim A. Killinger, and Ananias C. Diokno, “Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors,” Advances in Urology, vol. 2012, Article ID 276501, 8 pages, 2012. doi:10.1155/2012/276501