Abstract #300103

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2002 Program page
JSM 2002 Abstract #300103
Activity Number: 191
Type: Invited
Date/Time: Tuesday, August 13, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical & Engineering Sciences*
Abstract - #300103
Title: Prediction and Classification by Partial Least Squares Using Gene Expression Data
Author(s): David Rocke*+ and Danh Nguyen
Affiliation(s): University of California, Davis and Texas A&M University
Address: 2343 Academic Surge Building, 1 Shields Avenue, Davis, California, 95616,
Keywords: dimension reduction ; microarray ; principal components ; survival analysis
Abstract:

One major challenge in using gene expression data to predict and classify is the high dimensionality of the data. Typically, the number of samples may be in the tens to hundreds, and the number of variables (genes) may be in the thousands. In such cases, dimension reduction or variable selection is required. We review the application of partial least squares as a method of dimension reduction for use with gene expression data, and show how it can be used for classification and survival analysis, as well as for prediction of uncensored quantitative variables.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2002 program

JSM 2002

For information, contact meetings@amstat.org or phone (703) 684-1221.

If you have questions about the Continuing Education program, please contact the Education Department.

Revised March 2002