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Activity Number: 438
Type: Contributed
Date/Time: Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
Sponsor: Health Policy Statistics Section
Abstract - #308989
Title: F-Tests in Incomplete Data for Multiple Regression Set-Up
Author(s): Ashok Chaurasia*+ and Ofer Harel
Companies: Univeristy of Connecticut and University of Connecticut
Keywords: Incomplete Data ; Multiple Imputation ; Model Selection ; (Partial and Global) F-test ; Multiple Linear Regression
Abstract:

Tests for regression coefficients such as the partial F-test are common is applied research. When dealing with incomplete data, the task of conducting F-tests remains elusive. In this paper we propose a method based on the coefficient of determination to perform partial F-tests with multiply imputed data. Our proposed method can be applied for conducting the "global" F-test (test for all regression coefficients equal to zero), partial F-test (for one or more coefficients, but not all, equal zero), or for equality of regression coefficients. The proposed method is evaluated using simulated data and applied to a health related data.


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