Automatic regrouping of strata in the Goodness-of-Fit chi-square test
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Automatic regrouping of strata in the Goodness-of-Fit chi-square test

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Automatic regrouping of strata in the Goodness-of-Fit chi-square test

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dc.contributor.author Nuñez Antón, Vicente
dc.contributor.author Pérez-Salamero González, Juan Manuel
dc.contributor.author egúlez Castillo, Marta
dc.contributor.author Ventura Marco, Manuel
dc.contributor.author Vidal Meliá, Carlos
dc.date.accessioned 2019-11-06T11:28:28Z
dc.date.available 2019-11-06T11:28:28Z
dc.date.issued 2019
dc.identifier.uri https://hdl.handle.net/10550/72036
dc.description.abstract Pearson'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.language.iso eng
dc.relation.ispartof Sort-Statistics And Operations Research Transactions, 2019, vol. 43, num. 1, p. 113-142
dc.rights.uri info:eu-repo/semantics/openAccess
dc.source Nuñez Antón, Vicente Pérez-Salamero González, Juan Manuel egúlez Castillo, Marta Ventura Marco, Manuel Vidal Meliá, Carlos 2019 Automatic regrouping of strata in the Goodness-of-Fit chi-square test Sort-Statistics And Operations Research Transactions 43 1 113 142
dc.subject Economia
dc.subject Finances
dc.title Automatic regrouping of strata in the Goodness-of-Fit chi-square test
dc.type info:eu-repo/semantics/article
dc.date.updated 2019-11-06T11:28:29Z
dc.identifier.doi https://doi.org/10.2436/20.8080.02.83
dc.identifier.idgrec 135025

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