Abstract Details
Activity Number:
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175
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Type:
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Contributed
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Date/Time:
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Monday, August 10, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract #314954
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View Presentation
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Title:
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Estimating Power for Interaction Tests in Logistic Regression: A Case Study of Tobacco Cessation Among Cancer Survivors
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Author(s):
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Zoran Bursac* and D. Keith Williams and C. Heath Gauss and Bob Klesges
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Companies:
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University of Tennessee Health Science Center and University of Arkansas for Medical Sciences and University of Arkansas for Medical Sciences and University of Tennessee Health Science Center
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Keywords:
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Logistic regression ;
Power ;
Sample size ;
Interaction
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Abstract:
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At the present time, researchers are limited in available methods to conduct power analysis for an interaction term between two main variables of interest in a study that utilizes logistic regression. We propose a method and a SAS macro tool for estimating the power for the beta coefficient associated with an interaction term in a logistic regression model. This method empirically calculates the power for an interaction term, based on cell counts from a 2x2x2 table, and several other intuitive input parameters. We illustrate the method with an example from an RCT of tobacco cessation among cancer survivors, which investigates interaction between two-level treatment assignment and cancer staging.
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Authors who are presenting talks have a * after their name.
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