Local influence in estimating equations

dc.creatorVENEZUELA, Maria Kelly
dc.creatorSANDOVAL, Monica Carneiro
dc.creatorBOTTER, Denise Aparecida
dc.date.accessioned2012-10-20T04:44:12Z
dc.date.accessioned2018-07-04T15:46:03Z
dc.date.available2012-10-20T04:44:12Z
dc.date.available2018-07-04T15:46:03Z
dc.date.created2012-10-20T04:44:12Z
dc.date.issued2011
dc.identifierCOMPUTATIONAL STATISTICS & DATA ANALYSIS, v.55, n.4, p.1867-1883, 2011
dc.identifier0167-9473
dc.identifierhttp://producao.usp.br/handle/BDPI/30443
dc.identifier10.1016/j.csda.2010.10.020
dc.identifierhttp://dx.doi.org/10.1016/j.csda.2010.10.020
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1627082
dc.description.abstractLocal influence diagnostics based on estimating equations as the role of a gradient vector derived from any fit function are developed for repeated measures regression analysis. Our proposal generalizes tools used in other studies (Cook, 1986: Cadigan and Farrell, 2002), considering herein local influence diagnostics for a statistical model where estimation involves an estimating equation in which all observations are not necessarily independent of each other. Moreover, the measures of local influence are illustrated with some simulated data sets to assess influential observations. Applications using real data are presented. (C) 2010 Elsevier B.V. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCIENCE BV
dc.relationComputational Statistics & Data Analysis
dc.rightsCopyright ELSEVIER SCIENCE BV
dc.rightsrestrictedAccess
dc.subjectDiagnostic techniques
dc.subjectLocal influence
dc.subjectGeneralized estimating equations
dc.subjectRepeated measures
dc.subjectLongitudinal data
dc.titleLocal influence in estimating equations
dc.typeArtículos de revistas


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