Abstract Details
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Activity Number:
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438
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Health Policy Statistics Section
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| Abstract - #308966 |
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Title:
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Comparing Nested Regression Coefficients in Incomplete Data
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Author(s):
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Chantal Larose*+ and Ofer Harel and Jun Yan
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Companies:
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University of Connecticut Department of Statistics and University of Connecticut and University of Connecticut
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Keywords:
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missing data ;
multiple imputation ;
nested regression models
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Abstract:
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Comparing regression coefficients between nested models is of great practical interest when two explanations of a given phenomenon are specified as linear models. Methods for comparing such nested regression coefficients have been established when the data is complete. We use multiple imputation to extend existing procedures to incomplete data. Simulations and data example illustrate the problem and compare results to the complete case analysis. This is a joint work with Dr. Ofer Harel and Dr. Jun Yan.
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