Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/395
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fitzmaurice, Garrett | - |
dc.contributor.author | Lipsitz, Stuart | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | IBRAHIM, Joseph | - |
dc.date.accessioned | 2004-10-29T08:56:03Z | - |
dc.date.available | 2004-10-29T08:56:03Z | - |
dc.date.issued | 2001 | - |
dc.identifier.citation | Biometrics, 51(1). p. 15-21 | - |
dc.identifier.issn | 0006-341X | - |
dc.identifier.uri | http://hdl.handle.net/1942/395 | - |
dc.description.abstract | This paper considers the impact of bias in the estimation of the association parameters for longitudinal binary responses when there are drop-outs. A number of different estimating equation approaches are considered for the case where drop-out cannot be assumed to be a completely random process. In particular, standard generalized estimating equations (GEE), GEE based on conditional residuals, GEE based on multivariate normal estimating equations for the covariance matrix, and second-order estimating equations (GEEZ) are examined. These different GEE estimators are compared in terms of finite sample and asymptotic bias under a variety of drop-out processes. Finally, the relationship between bias in the estimation of the association parameters and bias in the estimation of the mean parameters is explored. | - |
dc.description.abstract | Ce papier considere l’impact du biais dans l’estimation des parametres d’association sur des rBponses binaires longitudinales en presence de donnBes manquantes. Differentes approches par des Bquations d’estimation sont envisaghes dans le cas ou les donnBes manquantes ne peuvent pas Gtre supposBes issues d’un processus de randomisation. En particulier des Bquations d’estimation gBnBralisBes standards (GEE) (Liang and Zeger, 1986; Prentice, 1988), des GEE B partir de rhsidus conditionnels (Carey et al., 1993; Lipsitz and Fitzmaurice, 1996), des GEE B partir d’kquations d’estimation normales multivaribes pour la matrice de covariance et des Bquations d’estimation du second ordre (GEES) (Liang, Zeger and et Qaqish, 1992) sont examinhes. Ces diffhrents GEE estimateurs sont compares en terme d’hchantillon fini et de biais asymp- totique avec diffkrents processus de prbence de donnhes man- quantes. Finalement la relation entre le biais de l’estimation des paramktres d’association et le biais dans l’estimation des paramiètres moyen est BtudiB. | - |
dc.description.abstract | Ce papier considere l’impact du biais dans l’estimation des parametres d’association sur des rBponses binaires longitudinales en presence de donnBes manquantes. Differentes approches par des Bquations d’estimation sont envisaghes dans le cas ou les donnBes manquantes ne peuvent pas Gtre supposBes issues d’un processus de randomisation. En particulier des Bquations d’estimation gBnBralisBes standards (GEE) (Liang and Zeger, 1986; Prentice, 1988), des GEE B partir de rhsidus conditionnels (Carey et al., 1993; Lipsitz and Fitzmaurice, 1996), des GEE B partir d’kquations d’estimation normales multivaribes pour la matrice de covariance et des Bquations d’estimation du second ordre (GEES) (Liang, Zeger and et Qaqish, 1992) sont examinhes. Ces diffhrents GEE estimateurs sont compares en terme d’hchantillon fini et de biais asymp- totique avec diffkrents processus de prbence de donnhes man- quantes. Finalement la relation entre le biais de l’estimation des paramktres d’association et le biais dans l’estimation des paramiètres moyen est BtudiB. | - |
dc.description.sponsorship | The authors thank the associate editor and the referees for their helpful comments and suggestions. This research was supported by grants ES07142, GM29745, and MH17119 from the National Institutes of Health (USA) and by funding from the Nationaal Fonds voor Wetenschappelijk Onderzoek (Bel- gium). | - |
dc.language.iso | en | - |
dc.publisher | INTERNATIONAL BIOMETRIC SOC | - |
dc.subject | Longitudinal data | - |
dc.subject | Missing data | - |
dc.subject.other | generalized estimating equations; missing data; repeated measures | - |
dc.title | Bias in estimating association parameters for longitudinal binary responses with drop-outs | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 21 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 15 | - |
dc.identifier.volume | 51 | - |
local.bibliographicCitation.jcat | A1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1111/j.0006-341X.2001.00015.x | - |
dc.identifier.isi | 000167376900003 | - |
item.fullcitation | Fitzmaurice, Garrett; Lipsitz, Stuart; MOLENBERGHS, Geert & IBRAHIM, Joseph (2001) Bias in estimating association parameters for longitudinal binary responses with drop-outs. In: Biometrics, 51(1). p. 15-21. | - |
item.accessRights | Restricted Access | - |
item.fulltext | With Fulltext | - |
item.contributor | Fitzmaurice, Garrett | - |
item.contributor | Lipsitz, Stuart | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | IBRAHIM, Joseph | - |
item.validation | ecoom 2002 | - |
crisitem.journal.issn | 0006-341X | - |
crisitem.journal.eissn | 1541-0420 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Fitzmaurice_et_al-2001-Biometrics.pdf Restricted Access | Published version | 713.91 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
17
checked on Sep 2, 2020
WEB OF SCIENCETM
Citations
18
checked on Oct 4, 2024
Page view(s)
62
checked on Sep 6, 2022
Download(s)
50
checked on Sep 6, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.