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http://hdl.handle.net/1942/7996
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DC Field | Value | Language |
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dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | BEUNCKENS, Caroline | - |
dc.contributor.author | SOTTO, Cristina | - |
dc.contributor.author | Kenward, Michael G. | - |
dc.date.accessioned | 2008-03-14T10:38:32Z | - |
dc.date.available | 2008-03-14T10:38:32Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 70. p. 371-388 | - |
dc.identifier.issn | 1369-7412 | - |
dc.identifier.uri | http://hdl.handle.net/1942/7996 | - |
dc.description.abstract | Over the last decade a variety of models to analyse incomplete multivariate and longitudinal data have been proposed, many of which allowing for the missingness to be not at random, in the sense that the unobserved measurements influence the process governing missingness, in addition to influences coming from observed measurements and/or covariates. The fundamental problems that are implied by such models, to which we refer as sensitivity to unverifiable modelling assumptions, has, in turn, sparked off various strands of research in what is now termed sensitivity analysis. The nature of sensitivity originates from the fact that a missingness not at random (MNAR) model is not fully verifiable from the data, rendering the empirical distinction between MNAR and missingness at random (MAR), where only covariates and observed outcomes influence missingness, difficult or even impossible, unless we are willing to accept the posited MNAR model in an unquestioning way. We show that the empirical distinction between MAR and MNAR is not possible, in the sense that each MNAR model fit to a set of observed data can be reproduced exactly by an MAR counterpart. Of course, such a pair of models will produce different predictions of the unobserved outcomes, given the observed outcomes. Theoretical considerations are supplemented with an illustration that is based on the Slovenian public opinion survey, which has been analysed before in the context of sensitivity analysis. | - |
dc.description.sponsorship | Ivy Jansen and Geert Molenberghs gratefully acknowledge support from Fonds Wetenschappelijk Onderzoek-Vlaanderen research project G.0002.98 ‘Sensitivity analysis for incomplete and coarse data’ and from Interuniversity Attraction Pole research network P6/03 of the Belgian Government (Belgian science policy). | - |
dc.format.extent | 189967 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | BLACKWELL PUBLISHING | - |
dc.rights | (C) 2008 Royal Statistical Society | - |
dc.subject.other | contingency table; ignorability; missing completely at random; pattern–mixturemodel; selection model; shared parameter model | - |
dc.subject.other | contingency table; ignorability; missing completely at random; pattern-mixture model; selection model; shared parameter model | - |
dc.title | Every missingness not at random model has a missingness at random counterpart with equal fit | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 388 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 371 | - |
dc.identifier.volume | 70 | - |
local.format.pages | 18 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Univ Hasselt, Ctr Stat, B-3590 Diepenbeek, Belgium. Univ London London Sch Hyg & Trop Med, London WC1E 7HT, England.Molenberghs, G, Univ Hasselt, Ctr Stat, Agoralaan 1, B-3590 Diepenbeek, Belgium.geert.molenberghs@uhasselt.be | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1111/j.1467-9868.2007.00640.x | - |
dc.identifier.isi | 000252964100005 | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | BEUNCKENS, Caroline | - |
item.contributor | SOTTO, Cristina | - |
item.contributor | Kenward, Michael G. | - |
item.fullcitation | MOLENBERGHS, Geert; BEUNCKENS, Caroline; SOTTO, Cristina & Kenward, Michael G. (2008) Every missingness not at random model has a missingness at random counterpart with equal fit. In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 70. p. 371-388. | - |
item.accessRights | Open Access | - |
item.fulltext | With Fulltext | - |
item.validation | ecoom 2009 | - |
crisitem.journal.issn | 1369-7412 | - |
crisitem.journal.eissn | 1467-9868 | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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GeertMolenberghs1.pdf | Peer-reviewed author version | 185.51 kB | Adobe PDF | View/Open |
every.pdf Restricted Access | Published version | 716.59 kB | Adobe PDF | View/Open Request a copy |
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