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dc.contributor.authorBarnett, Adrian G
dc.contributor.authorMcElwee, Paul
dc.contributor.authorNathan, Andrea
dc.contributor.authorBurton, Nicola W
dc.contributor.authorTurrell, Gavin
dc.date.accessioned2020-10-26T04:03:09Z
dc.date.available2020-10-26T04:03:09Z
dc.date.issued2017
dc.identifier.issn2044-6055
dc.identifier.doi10.1136/bmjopen-2017-01728
dc.identifier.urihttp://hdl.handle.net/10072/398688
dc.description.abstractObjectives: To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as 'item missing'. Design: Observational study of longitudinal data. Setting: Residents of Brisbane, Australia. Participants: 6901 people aged 40-65 years in 2007. Materials and methods: We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants' characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Results: Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Conclusions: Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherBMJ Publishing Group
dc.publisher.placeUnited Kingdom
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto9
dc.relation.ispartofissue10
dc.relation.ispartofjournalBMJ Open
dc.relation.ispartofvolume7
dc.subject.fieldofresearchClinical sciences
dc.subject.fieldofresearchHealth services and systems
dc.subject.fieldofresearchPublic health
dc.subject.fieldofresearchOther health sciences
dc.subject.fieldofresearchcode3202
dc.subject.fieldofresearchcode4203
dc.subject.fieldofresearchcode4206
dc.subject.fieldofresearchcode4299
dc.subject.keywordsScience & Technology
dc.subject.keywordsLife Sciences & Biomedicine
dc.subject.keywordsMedicine, General & Internal
dc.subject.keywordsGeneral & Internal Medicine
dc.subject.keywordsMULTIPLE IMPUTATION
dc.titleIdentifying patterns of item missing survey data using latent groups: an observational study
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationBarnett, AG; McElwee, P; Nathan, A; Burton, NW; Turrell, G, Identifying patterns of item missing survey data using latent groups: an observational study, BMJ Open, 2017, 7 (10), pp. 1-9
dcterms.licensehttp://creativecommons.org/licenses/by-nc/4.0/
dc.date.updated2020-10-25T23:59:39Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2017. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
gro.hasfulltextFull Text
gro.griffith.authorBurton, Nicola W.


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