A study of partial F tests for multiple linear regression models

Authors:
Mortaza Jamshidian;Robert I. Jennrich;Wei Liu
Affiliations:
Department of Mathematics, California State University, Fullerton, CA 92834, USA;Department of Mathematics, University of California, Los Angeles, CA, USA;Statistical Sciences Research Institute and School of Maths, The University, Southampton, SO17 1BJ, UK
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

Partial F tests play a central role in model selections in multiple linear regression models. This paper studies the partial F tests from the view point of simultaneous confidence bands. It first shows that there is a simultaneous confidence band associated naturally with a partial F test. This confidence band provides more information than the partial F test and the partial F test can be regarded as a side product of the confidence band. This view point of confidence bands also leads to insights of the major weakness of the partial F tests, that is, a partial F test requires implicitly that the linear regression model holds over the entire range of the covariates in concern. Improved tests are proposed and they are induced by simultaneous confidence bands over restricted regions of the covariates. Power comparisons between the partial F tests and the new tests have been carried out to assess when the new tests are more or less powerful than the partial F tests. Computer programmes have been developed for easy implements of these new confidence band based inferential methods. An illustrative example is provided.