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Activity Number: 248
Type: Contributed
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #315737
Title: Improving Estimates of Biological Age Using Ensemble-Based Prediction Models in Genomic Data Applications
Author(s): Wendy Shih* and Steve Horvath
Companies: UCLA Fielding School of Public Health and UCLA
Keywords: biomarkers of aging ; genomics
Abstract:

Biological age (BA) as opposed to chronological age (CA) is meant to measure the true aging process of an individual. The hope is that BA is better than CA when it comes to predicting mortality or age related functional decline. We evaluated and adapted techniques from Klemera and Doubal (2006) and proposed a novel ensemble based approach in estimating biological age. However, several simulations had shown that the Klemera and Doubal method may produce unreliable estimates especially in the presence of extreme outliers. Though the ensemble based approach mitigated the issue, it was not without limitations. Here, we propose a method to produce more reliable estimates even in the presence of outliers for the Klemera and Doubal approach and, consequently, improve the accuracy of our ensemble based approach as well. Lastly, we evaluated and compared the performance of each method including our improved ensemble based model in simulated and real data.


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