title: Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.
abstract: Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data.
authors.affiliation: Department of Statistics, University of Connecticut, Storrs, CT 06269-4120, U.S.A.. achaurasia.uconn@gmail.com.
authors.forename: Ashok
authors.initials: A
authors.lastname: Chaurasia
authors.forename: Ofer
authors.initials: O
authors.lastname: Harel
mesh_terms: D000704:Analysis of Variance; D001699:Biometry / Q000379:methods; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016014:Linear Models; D012044:Regression Analysis; D012107:Research Design; D000092864:Suicide Prevention
keywords: F-tests; coefficient of determination; incomplete data; multiple imputation; multiple regression