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dc.contributor.authorNúñez-Antón, Vicente
dc.contributor.authorPérez-Salamero, Juan Manuel
dc.contributor.authorRegúlez-Castillo, Marta
dc.contributor.authorVentura-Marco, Manuel
dc.contributor.authorVidal-Meliá, Carlos
dc.date.accessioned2020-02-24T16:22:25Z
dc.date.available2020-02-24T16:22:25Z
dc.date.issued2019-06-11
dc.identifier.citationNúñez-Antón, V. [et al.]. Automatic regrouping of strata in the goodness-of-fit chi-square test. "SORT", 11 Juny 2019, vol. 1, p. 113-142.
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2117/178516
dc.description.abstractPearson’s chi-square test is widely employed in social and health sciences to analyse categorical data and contingency tables. For the test to be valid, the sample size must be large enough to provide a minimum number of expected elements per category. This paper develops functions for regrouping strata automatically, thus enabling the goodness-of-fit test to be performed within an iterative procedure. The usefulness and performance of these functions is illustrated by means of a simulation study and the application to different datasets. Finally, the iterative use of the functions is applied to the Continuous Sample of Working Lives, a dataset that has been used in a considerable number of studies, especially on labour economics and the Spanish public pension system.
dc.format.extent30 p.
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.otherGoodness-of-fit chi-square test
dc.subject.otherstatistical software
dc.subject.otherVisual Basic for Applications
dc.subject.otherMathematica
dc.subject.otherContinuous Sample of Working Lives
dc.titleAutomatic regrouping of strata in the goodness-of-fit chi-square test
dc.typeArticle
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62G Nonparametric inference
dc.subject.amsClassificació AMS::62 Statistics::62P Applications
dc.rights.accessOpen Access
local.citation.publicationNameSORT
local.citation.volume1
local.citation.startingPage113
local.citation.endingPage142


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain