Latent residual analysis in binary regression with skewed link

Farias, Rafael B. A.; Branco, Marcia D.

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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Latent residual analysis in binary regression with skewed link

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Author(s):	Farias, Rafael B. A. ^[1] ; Branco, Marcia D. ^[1] Total Authors: 2
Affiliation:	^[1] Univ Sao Paulo, Dept Estat, BR-05315970 Sao Paulo - Brazil Total Affiliations: 1
Document type:	Journal article
Source:	BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS; v. 26, n. 4, p. 344-357, NOV 2012.
Web of Science Citations:	0
Abstract
Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset. (AU)

FAPESP's process:	07/03598-3 - Bayesian analysis in multivariate skew-probit models
Grantee:	Rafael Bráz Azevedo Farias
Support Opportunities:	Scholarships in Brazil - Doctorate

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