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Abstract Details
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Activity Number:
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412
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #306053 |
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Title:
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Explained Variation for the Proportional Hazards Mixed-Effects Model
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Author(s):
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Gordon Honerkamp-Smith*+
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Companies:
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Address:
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4435 Nobel Dr, San Diego, CA, 92122, United States
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Keywords:
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survival ;
Cox ;
proportional ;
hazard ;
explained ;
variation
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Abstract:
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The notion of explained variation quantifies the extent to which a given model accounts for variation observed in the data. The R-squared coefficient in linear regression is perhaps the most well-known example, but such measures have been proposed for many other settings, including linear mixed-effects models and the Cox proportional hazards model in Survival Analysis. In this paper, we propose several measures of explained variation for the proportional hazards mixed-effects model--a powerful generalization of the Cox model proposed by Xu and Vaida in 2000. We examine their properties and compare their performance on simulated data, and demonstrate their usefulness for model selection using a lung-cancer multi-center clinical trials data set.
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Authors who are presenting talks have a * after their name.
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