Access

You are not currently logged in.

Access JSTOR through your library or other institution:

login

Log in through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Concepts and Suggestions for Robust Regression Analysis

Bruce Western
American Journal of Political Science
Vol. 39, No. 3 (Aug., 1995), pp. 786-817
DOI: 10.2307/2111654
Stable URL: http://www.jstor.org/stable/2111654
Page Count: 32
  • Read Online (Free)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Concepts and Suggestions for Robust Regression Analysis
Preview not available

Abstract

Robust methods for regression yield parameter estimates that are insensitive to small departures in the data from the assumed model. A review of some basic ideas of robust estimation focuses on a class of techniques called M-estimators that discount the impact of outlying observations. These ideas are extended to three practically important areas: (1) some simple methods for inference for robust estimators are described; (2) a more general class of robust estimators for generalized linear models is then introduced; (3) the high breakdown least median of squares method is presented. Applications from comparative and American politics illustrate ideas in these areas.

Page Thumbnails

  • Thumbnail: Page 
[786]
    [786]
  • Thumbnail: Page 
787
    787
  • Thumbnail: Page 
788
    788
  • Thumbnail: Page 
789
    789
  • Thumbnail: Page 
790
    790
  • Thumbnail: Page 
791
    791
  • Thumbnail: Page 
792
    792
  • Thumbnail: Page 
793
    793
  • Thumbnail: Page 
794
    794
  • Thumbnail: Page 
795
    795
  • Thumbnail: Page 
796
    796
  • Thumbnail: Page 
797
    797
  • Thumbnail: Page 
798
    798
  • Thumbnail: Page 
799
    799
  • Thumbnail: Page 
800
    800
  • Thumbnail: Page 
[801]
    [801]
  • Thumbnail: Page 
802
    802
  • Thumbnail: Page 
803
    803
  • Thumbnail: Page 
804
    804
  • Thumbnail: Page 
805
    805
  • Thumbnail: Page 
806
    806
  • Thumbnail: Page 
807
    807
  • Thumbnail: Page 
808
    808
  • Thumbnail: Page 
809
    809
  • Thumbnail: Page 
810
    810
  • Thumbnail: Page 
811
    811
  • Thumbnail: Page 
812
    812
  • Thumbnail: Page 
813
    813
  • Thumbnail: Page 
814
    814
  • Thumbnail: Page 
815
    815
  • Thumbnail: Page 
816
    816
  • Thumbnail: Page 
817
    817