Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42890
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dc.contributor.authorGómez Déniz, Emilioen_US
dc.date.accessioned2018-11-21T11:33:38Z-
dc.date.available2018-11-21T11:33:38Z-
dc.date.issued2013en_US
dc.identifier.issn0266-4763en_US
dc.identifier.urihttp://hdl.handle.net/10553/42890-
dc.description.abstractThis paper proposes a simple and flexible count data regression model which is able to incorporate overdispersion (the variance is greater than the mean) and which can be considered a competitor to the Poisson model. As is well known, this classical model imposes the restriction that the conditional mean of each count variable must equal the conditional variance. Nevertheless, for the common case of well-dispersed counts the Poisson regression may not be appropriate, while the count regression model proposed here is potentially useful. We consider an application to model counts of medical care utilization by the elderly in the USA using a well-known data set from the National Medical Expenditure Survey (1987), where the dependent variable is the number of stays after hospital admission, and where 10 explanatory variables are analyseden_US
dc.languageengen_US
dc.publisher0266-4763
dc.relation.ispartofJournal of Applied Statisticsen_US
dc.sourceJournal of Applied Statistics[ISSN 0266-4763],v. 40, p. 2760-2770en_US
dc.subject530202 Modelos econométricosen_US
dc.subject.otherModelos econométricosen_US
dc.subject.otherSalud públicaen_US
dc.titleA new discrete distribution: Properties and applications in medical careen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1080/02664763.2013.827161
dc.identifier.scopus84885387215-
dc.identifier.isi000325198000014
dc.contributor.authorscopusid15050089900
dc.description.lastpage2770-
dc.description.firstpage2760-
dc.relation.volume40-
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Artículoen_US
dc.contributor.daisngid3977316
dc.contributor.wosstandardWOS:Deniz, EG
dc.date.coverdateDiciembre 2013
dc.identifier.ulpgces
dc.description.sjr0,542
dc.description.jcr0,453
dc.description.sjrqQ3
dc.description.jcrqQ4
dc.description.scieSCIE
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR TIDES- Técnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-5072-7908-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.fullNameGómez Déniz, Emilio-
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