Improved transformed deviance statistic for testing a logistic regression model
In logistic regression models, we consider the deviance statistic (the log likelihood ratio statistic) D as a goodness-of-fit test statistic. In this paper, we show the derivation of an expression of asymptotic expansion for the distribution of D under a null hypothesis. Using the continuous term of the expression, we obtain a Bartlett-type transformed statistic that improves the speed of convergence to the chi-square limiting distribution of D. By numerical comparison, we find that the transformed statistic performs much better than D. We also give a real data example of being more reliable than D for testing a hypothesis.
Year of publication: |
2011
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Authors: | Taneichi, Nobuhiro ; Sekiya, Yuri ; Toyama, Jun |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 102.2011, 9, p. 1263-1279
|
Publisher: |
Elsevier |
Keywords: | Bartlett adjustment Deviance Edgeworth expansion Logistic regression |
Saved in:
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