Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMartínez-Rodríguez, Ana M.-
dc.contributor.authorConde-Sánchez, Antonio-
dc.contributor.authorOlmo-Jiménez, María J.-
dc.description.abstractStandard Poisson and negative binomial truncated regression models for count data include the regressors in the mean of the non-truncated distribution. In this paper, a new approach is proposed so that the explanatory variables determine directly the truncated mean. The main advantage is that the regression coefficients in the new models have a straightforward interpretation as the effect of a change in a covariate on the mean of the response variable. A simulation study has been carried out in order to analyze the performance of the proposed truncated regression models versus the standard ones showing that coefficient estimates are now more accurate in the sense that the standard errors are always lower. Also, the simulation study indicates that the estimates obtained with the standard models are biased. An application to real data illustrates the utility of the introduced truncated models in a hurdle model. Although in the example there are slight differences in the results between the two approaches, the proposed one provides a clear interpretation of the coefficient estimates.es_ES
dc.relation.ispartofAStA Advances in Statistical Analysis [2019]; [103]: [503–526]es_ES
dc.subjectCount dataes_ES
dc.subjectHurdle modeles_ES
dc.subjectNegative binomial regressiones_ES
dc.subjectPoisson regressiones_ES
dc.subjectTruncated modelses_ES
dc.titleA new approach to truncated regression for count dataes_ES
Appears in Collections:DEIO-Artículos

Files in This Item:
File Description SizeFormat 
truncatedreviewed.pdfVersión aceptada473,18 kBAdobe PDFView/Open

This item is protected by original copyright

Items in RUJA are protected by copyright, with all rights reserved, unless otherwise indicated.