Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Journal of Applied Sciences
  Year: 2013 | Volume: 13 | Issue: 6 | Page No.: 828-836
DOI: 10.3923/jas.2013.828.836
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Modified Standardized Pearson Residual for the Identification of Outliers in Logistic Regression Model

Habshah Midi and Syaiba Balqish Ariffin

Abstract:
Detection of outlier based on standardized Pearson residuals has gained widespread use in logistic regression model in the presence of a single outlier. An innovation attempts in the same direction but dealing for a group of outliers have been made using generalized standardized Pearson residual which requires a graphical or a robust estimator to find suspected outliers to form a group deletion. In this study, an alternative measure namely modified standardized Pearson residual is derived from the robust logistic diagnostic. The weakness of standardized Pearson residuals and the usefulness of generalized standardized Pearson residual and modified standardized Pearson residual are examined through several real examples and Monte Carlo simulation study. The results of this study signify that the generalized standardized Pearson residual and the modified standardized Pearson residual perform equally good in identifying a group of outliers.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    Detection of Outliers and Influential Observations in Binary Logistic Regression: An Empirical Study
  •    Robust Logistic Diagnostic for the Identification of High Leverage Points in Logistic Regression Model
How to cite this article:

Habshah Midi and Syaiba Balqish Ariffin, 2013. Modified Standardized Pearson Residual for the Identification of Outliers in Logistic Regression Model. Journal of Applied Sciences, 13: 828-836.

DOI: 10.3923/jas.2013.828.836

URL: https://scialert.net/abstract/?doi=jas.2013.828.836

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 

Curve Bottom