Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20865
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dc.contributor.authorRAKHMAWATI, Trias Wahyuni-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorVERBEKE, Geert-
dc.contributor.authorFAES, Christel-
dc.date.accessioned2016-03-31T15:00:18Z-
dc.date.available2016-03-31T15:00:18Z-
dc.date.issued2015-
dc.identifier.citationJournal of applied statistics, 43 (9), p. 1722-1737-
dc.identifier.issn0266-4763-
dc.identifier.urihttp://hdl.handle.net/1942/20865-
dc.description.abstractWe develop local influence diagnostics to detect influential subjects when generalized linear mixed models are fitted to incomplete longitudinal overdispersed count data. The focus is on the influence stemming from the dropout model specification. In particular, the effect of small perturbations around an MAR specification are examined. The method is applied to data from a longitudinal clinical trial in epileptic patients. The effect on models allowing for overdispersion is contrasted with that on models that do not.-
dc.description.sponsorshipFinancial support from the IAP research network #P7/06 of the Belgian Government (Belgian Science Policy) is gratefully acknowledged.-
dc.language.isoen-
dc.rights© 2016 Taylor & Francis-
dc.subject.othercombined model; missing data; Poisson–Gamma–Normal model; Poisson–Normal model; sensitivity analysis-
dc.titleLocal Influence Diagnostics for Incomplete Overdispersed Longitudinal Counts-
dc.typeJournal Contribution-
dc.identifier.epage1737-
dc.identifier.issue9-
dc.identifier.spage1722-
dc.identifier.volume43-
local.format.pages16-
local.bibliographicCitation.jcatA1-
dc.description.notesMolenberghs, G (reprint author), Univ Hasselt, I BioStat, Diepenbeek, Belgium. geert.molenberghs@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1080/02664763.2015.1117594-
dc.identifier.isi000375002600010-
dc.identifier.urlhttps://www.researchgate.net/publication/295401290_Local_influence_diagnostics_for_incomplete_overdispersed_longitudinal_counts-
item.validationecoom 2017-
item.fullcitationRAKHMAWATI, Trias Wahyuni; MOLENBERGHS, Geert; VERBEKE, Geert & FAES, Christel (2015) Local Influence Diagnostics for Incomplete Overdispersed Longitudinal Counts. In: Journal of applied statistics, 43 (9), p. 1722-1737.-
item.fulltextWith Fulltext-
item.contributorRAKHMAWATI, Trias Wahyuni-
item.contributorMOLENBERGHS, Geert-
item.contributorVERBEKE, Geert-
item.contributorFAES, Christel-
item.accessRightsRestricted Access-
crisitem.journal.issn0266-4763-
crisitem.journal.eissn1360-0532-
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