Improved transformed deviance statistic for testing a logistic regression model

Taneichi, Nobuhiro; Sekiya, Yuri; Toyama, Jun

Journal of Multivariate Analysis, 2011, 102(9), 1263-1279

Permalink : https://hdl.handle.net/2115/47351

このアイテムのアクセス数:845件（2026-10-18 12:57 集計）

ファイル	フォーマット	サイズ	閲覧回数	説明
JMA102-9_1263-1279	pdf	277 KB	1,077

アクセス権	open access
URI	https://hdl.handle.net/2115/47351
タイトル	Improved transformed deviance statistic for testing a logistic regression model
著者	Taneichi, Nobuhiro ; Sekiya, Yuri ; Toyama, Jun
著者名 Taneichi, Nobuhiro
著者名 Sekiya, Yuri
e-Rad_Researcher 60197960 著者名 Toyama, Jun
言語	英語
キーワード	Bartlett adjustment
	Deviance
	Edgeworth expansion
	Logistic regression
発行日	2011-10
出版者	Elsevier
収録物名	Journal of Multivariate Analysis
巻(号)	102(9)
ページ	1263-1279
抄録	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 D˜ that improves the speed of convergence to the chi-square limiting distribution of D. By numerical comparison, we find that the transformed statistic D˜ performs much better than D. We also give a real data example of D˜ being more reliable than D for testing a hypothesis.
資源タイプ	学術雑誌論文
出版タイプ	Accepted Manuscript
PISSN	0047-259X
関連情報 (isVersionOf)	出版社版DOI https://doi.org/10.1016/j.jmva.2011.04.010