Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/334
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLipsitz, Stuart R.-
dc.contributor.authorZhao, Lue Ping-
dc.contributor.authorMOLENBERGHS, Geert-
dc.date.accessioned2004-10-22T13:41:55Z-
dc.date.available2004-10-22T13:41:55Z-
dc.date.issued1998-
dc.identifier.citationJournal of the Royal Statistical Society Series B, 60(1). p. 127-144-
dc.identifier.issn1369-7412-
dc.identifier.urihttp://hdl.handle.net/1942/334-
dc.description.abstractIn this paper, we describe how to use multiple imputation semiparametrically to obtain estimates of parameters and their standard errors when some individuals have missing data. The methods given require the investigator to know or be able to estimate the process generating the missing data but requires no full distributional form for the data. The method is especially useful for non-standard problems, such as estimating the median when data are missing.-
dc.description.sponsorshipThe authors are grate ful for the support from the US National Institutes of Health grantsGM 29745, CA 55576 and CA 56670.-
dc.language.isoen-
dc.rights(C) 1998 Royal Statistical Society-
dc.subjectNon and semiparametric methods-
dc.subjectMissing data-
dc.subject.othercomplete cases; missing at random; missing data mechanism-
dc.titleA semi-parametric method of multiple imputation-
dc.typeJournal Contribution-
dc.identifier.epage144-
dc.identifier.issue1-
dc.identifier.spage127-
dc.identifier.volume60-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1111/1467-9868.00113-
dc.identifier.isi000073377900010-
item.contributorLipsitz, Stuart R.-
item.contributorZhao, Lue Ping-
item.contributorMOLENBERGHS, Geert-
item.validationecoom 1999-
item.fulltextWith Fulltext-
item.accessRightsRestricted Access-
item.fullcitationLipsitz, Stuart R.; Zhao, Lue Ping & MOLENBERGHS, Geert (1998) A semi-parametric method of multiple imputation. In: Journal of the Royal Statistical Society Series B, 60(1). p. 127-144.-
crisitem.journal.issn1369-7412-
crisitem.journal.eissn1467-9868-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
Lipsitz_et_al-1998-Journal_of_the_Royal_Statistical_Society__Series_B_(Statistical_Methodology).pdf
  Restricted Access
Published version373.36 kBAdobe PDFView/Open    Request a copy
Show simple item record

SCOPUSTM   
Citations

17
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

25
checked on Oct 12, 2024

Page view(s)

104
checked on Sep 7, 2022

Download(s)

90
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.