Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146601 | Journal of Multivariate Analysis | 2011 | 17 Pages |
Abstract
In logistic regression models, we consider the deviance statistic (the log likelihood ratio statistic) DD as a goodness-of-fit test statistic. In this paper, we show the derivation of an expression of asymptotic expansion for the distribution of DD under a null hypothesis. Using the continuous term of the expression, we obtain a Bartlett-type transformed statistic D̃ that improves the speed of convergence to the chi-square limiting distribution of DD. By numerical comparison, we find that the transformed statistic D̃ performs much better than DD. We also give a real data example of D̃ being more reliable than DD for testing a hypothesis.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Nobuhiro Taneichi, Yuri Sekiya, Jun Toyama,