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Computing Topics on Multiple Imputation in Big Identifiable Data Using R: An Application to Educational Research

2019-06-29Book part Restricted access
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dc.contributor.authorFerrão, Maria Eugénia
dc.contributor.authorPrata, Paula
dc.date.accessioned2020-01-27T11:21:36Z
dc.date.available2020-01-27T11:21:36Z
dc.date.issued2019-06-29
dc.description.abstractThis article shows how to conduct multiple imputation in big identifiable data for educational research purposes. The R statistical package and procedures to handle missing data applied for the purpose of this study were “Bay-lorEdPsych” and “mi”. Firstly, we checked that every dataset rejected the null hypothesis for Missing Completely At Random (MCAR), using the function “LittleMCAR”. Simulated and real data analyses were conducted. Results sug-gest that the improvement of the quality of imputation requires alternative methods to be developed.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFerrão M.E., Prata P. (2019) Computing Topics on Multiple Imputation in Big Identifiable Data Using R: An Application to Educational Research. In: Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science, vol 11621. Springer, Champt_PT
dc.identifier.doihttps://doi.org/10.1007/978-3-030-24302-9_2pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8731
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer, Champt_PT
dc.relationInstituto de Telecomunicações
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-030-24302-9_2pt_PT
dc.subjectMultiple imputationpt_PT
dc.subjectR programmingpt_PT
dc.subjectBig datapt_PT
dc.subjectEducation researchpt_PT
dc.titleComputing Topics on Multiple Imputation in Big Identifiable Data Using R: An Application to Educational Researchpt_PT
dc.typebook part
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50008%2F2019/PT
oaire.citation.endPage23pt_PT
oaire.citation.startPage12pt_PT
oaire.citation.titleLecture Notes in Computer Sciencept_PT
oaire.citation.volume11621pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFerrão
person.familyNamePrata
person.givenNameMaria Eugénia
person.givenNamePaula
person.identifier.ciencia-id651F-C1C8-44AD
person.identifier.orcid0000-0002-1317-0629
person.identifier.orcid0000-0002-3072-0186
person.identifier.ridA-2665-2011
person.identifier.scopus-author-id24075949800
person.identifier.scopus-author-id6506143567
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.embargofctCopyright cedido à editora no momento da publicaçãopt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublicationf32b6cd9-ea61-4de5-898c-d4e0d40a057f
relation.isAuthorOfPublication138a0dac-5e5d-466c-901d-4ed34f860403
relation.isAuthorOfPublication.latestForDiscoveryf32b6cd9-ea61-4de5-898c-d4e0d40a057f
relation.isProjectOfPublication11e7de42-6a06-4bc8-99c3-ce68de57dbda
relation.isProjectOfPublication.latestForDiscovery11e7de42-6a06-4bc8-99c3-ce68de57dbda

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