This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 360
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #309224
Title: Likelihood-Based Evaluation of Normalization Methods
Author(s): Sadhvi Khanna*+
Companies: The University of Arizona
Address: College of Public Health, Tucson, AZ, 85724-0001,
Keywords: normalization ; linear models ; genomics

In biomedical research, many technologies measure the relative intensity of each response. This type of measurement is highly multivariate and is often influenced by non-biologic sources of variation. Measurement methods such as DNA micro-array data, mass spectrometry, raman spectrometry and many more use normalization techniques to make the observations more analogous and remove the nuisance variation that is present when quantifying the data. These normalization methods are the most important step in the analysis of such data, however the there is no statistical guiding principle behind the choice of the method. Diagnostic plots are used to choose between the competing normalization techniques. The aim of this poster is to statistically evaluate the transformations used to normalize the data in the cases when the diagnostic plots are not precise.

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