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Activity Number: 69 - Highlights of the Canadian Journal of Statistics
Type: Invited
Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
Sponsor: SSC (Statistical Society of Canada)
Abstract #316697
Title: A Directional Look at F-Tests
Author(s): Nancy Reid* and Andrew McCormack
Companies: University of Toronto and Duke University
Keywords: conditional inference; directional testing; exponential families; linear regression

Directional testing of vector parameters, based on higher order approximations of likelihood theory, can ensure extremely accurate inference, even in high-dimensional settings where standard first order likelihood results can perform poorly. Here we explore examples of directional inference where the calculations can be simplified, and prove that in several classical situations the directional test reproduces exact results based on $F$-tests. These findings give a new interpretation of some classical results and support the use of directional testing in general models, where exact solutions are typically not available.

Authors who are presenting talks have a * after their name.

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