Graphical Methods for Investigating the Size and Power of Hypothesis Tests
AbstractSimple techniques for the graphical display of simulation evidence concerning the size and power of hypothesis tests are developed and illustrated. Three types of figures--called P value plots, P value discrepancy plots, and size-power curves--are discussed. Some Monte Carlo experiments on the properties of alternative forms of the information matrix test for linear regression models and probit models are used to illustrate these figures. Tests based on the outer-product-of-the-gradient regression generally perform much worse in terms of both size and power than efficient score tests. Copyright 1998 by Blackwell Publishers Ltd and The Victoria University of Manchester
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Bibliographic InfoArticle provided by University of Manchester in its journal The Manchester School of Economic & Social Studies.
Volume (Year): 66 (1998)
Issue (Month): 1 (January)
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Postal: Manchester M13 9PL
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Web page: http://www.socialsciences.manchester.ac.uk/disciplines/economics/
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Other versions of this item:
- Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Russell Davidson & James G. MacKinnon, 1980.
"Model Specification Tests Based on Artificial Linear Regressions,"
390, Queen's University, Department of Economics.
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- Davidson, R. & Mackinnon, J.G., 1996.
"The Size and Power of Bootstrap Tests,"
96a03, Universite Aix-Marseille III.
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