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Diagnostics for residual outliers using deviance component in binary logistic regression.


Citation

Ahmad, Sanizah and Midi, Habshah and Mohamed Ramli, Norazan (2011) Diagnostics for residual outliers using deviance component in binary logistic regression. World Applied Sciences Journal, 14 (8). pp. 1125-1130. ISSN 1818-4952; ESSN: 1991-6426

Abstract / Synopsis

Detection of outliers based on residuals has received great interest in logistic regression. These methods like Pearson residuals and deviance residuals are only reliable for identifying a single outlier but fails for multiple outlier due to the masking and swamping problems. Therefore it is necessary to detect these outliers and take appropriate measures to obtain a good fit. In this study, we developed a new diagnostic method on the identification of residual outliers in logistic regression based on deviance component. The performance of the proposed diagnostic method is investigated through numerical examples and Monte Carlo simulation study. The result indicates that the proposed method manages to correctly identify all the outliers.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
Publisher: IDOSI Publications
Keywords: Deviance residuals; Outliers; Pearson residuals; Deviance residuals; Simulation.
Depositing User: Nur Farahin Ramli
Date Deposited: 21 Nov 2013 07:42
Last Modified: 08 Oct 2015 04:17
URI: http://psasir.upm.edu.my/id/eprint/25295
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