cris.boxmetadata.label.title
Bayesian skew-probit regression for binary response data
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.january 2014
cris.boxmetadata.label.accesslevel
open access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Romeo J.
Rodrigues J.
Universidade de São Paulo
cris.boxmetadata.label.publisher
Brazilian Statistical Association
cris.boxmetadata.label.abstract
Since many authors have emphasized the need of asymmetric link functions to fit binary regression models, we propose in this work two new skew-probit link functions for the binary response variables. These link functions will be named power probit and reciprocal power probit due to the relation between them including the probit link as a special case. Also, the probit regressions are special cases of the models considered in this work. A Bayesian inference approach using MCMC is developed for real data suggesting that the link functions proposed here are more appropriate than other link functions used in the literature. In addition, simulation study show that the use of probit model will lead to biased estimate of the regression coefficient. © Brazilian Statistical Association, 2014.
cris.boxmetadata.label.citationstartpage
467
cris.boxmetadata.label.citationendpage
482
cris.boxmetadata.label.volume
28
cris.boxmetadata.label.issue
4
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Estadísticas, Probabilidad
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-84905256052
cris.boxmetadata.label.source
Brazilian Journal of Probability and Statistics
cris.boxmetadata.label.containerissn
01030752
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