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Abstract Details

Activity Number: 7
Type: Invited
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract - #303747
Title: Wavelet-Based Regression with Images as Predictors
Author(s): Todd Ogden*+
Companies: Columbia University
Address: Department of Biostatistics, Columbia University, New York, NY, 10032,
Keywords: functional data ; brain imaging ; wavelets

In many biomedical applications it is of interest to use imaging data or other very high dimensional data as predictors in regression models, e.g., to predict a patient's treatment outcome based on brain imaging data obtained at baseline. Obtaining meaningful fits in such problems requires some form of dimension reduction while taking into account the structure of the data. Wavelet analysis provides useful tools that can allow regression models to focus on important aspects of the images across a range of scales. This talk will demonstrate some methods for modeling such data and for data-adaptive selection of tuning parameters.

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