Identification of multiple influential observations in logistic regression

A. A. M. Nurunnabi, A.H.M. Rahmatullah Imon and M. Nasser

Journal of Applied Statistics, 2010, vol. 37, issue 10, 1605-1624

Abstract: The identification of influential observations in logistic regression has drawn a great deal of attention in recent years. Most of the available techniques like Cook's distance and difference of fits (DFFITS) are based on single-case deletion. But there is evidence that these techniques suffer from masking and swamping problems and consequently fail to detect multiple influential observations. In this paper, we have developed a new measure for the identification of multiple influential observations in logistic regression based on a generalized version of DFFITS. The advantage of the proposed method is then investigated through several well-referred data sets and a simulation study.

Keywords: generalized DFFITS; generalized Studentized Pearson residual; generalized weight; high leverage point; influential observation; masking; outlier; swamping (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1080/02664760903104307

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