DocumentCode :
1997584
Title :
Outlier detection in logistic regression and its application in medical data analysis
Author :
Ahmad, Sahar ; Ramli, Norazan Mohamed ; Midi, H.
Author_Institution :
Fac. of Comput. & Math. Sci., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear :
2012
fDate :
3-4 Dec. 2012
Firstpage :
503
Lastpage :
507
Abstract :
The application of logistic regression is widely used in medical research. The detection of outliers has become an essential part of logistic regression. It is often observed outliers have a considerable influence on the analysis results, which may lead the study to the wrong conclusions. Many procedures for the identification of outliers in logistic regression are available in the literature. In this paper, four methods for outlier detection have been investigated and compared through numerical examples.
Keywords :
biomedical engineering; data analysis; logistics; medical computing; regression analysis; logistic regression application; medical data analysis; medical research; outlier detection; detection; logistic regression; outlier; residual;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Humanities, Science and Engineering (CHUSER), 2012 IEEE Colloquium on
Conference_Location :
Kota Kinabalu
Print_ISBN :
978-1-4673-4615-3
Type :
conf
DOI :
10.1109/CHUSER.2012.6504365
Filename :
6504365
Link To Document :
بازگشت