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Missing data methods in longitudinal studies: a review Author info | Abstract | Publisher info | Download info | Related research | Statistics Joseph Ibrahim ()
Geert Molenberghs ()
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Article provided by Springer in its journal TEST .
Volume (Year): 18 (2009)
Issue (Month): 1 (May)
Pages: 1-43
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Handle: RePEc:spr:testjl:v:18:y:2009:i:1:p:1-43Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=120411
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Keywords: Expectation-maximization algorithm ; Incomplete data ; Missing completely at random ; Missing at random ; Missing not at random ; Pattern-mixture model ; Selection model ; Sensitivity analyses ; Shared-parameter model ; 62J05 ; 62J12 ; 62P10 ; References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.:
Chen, Qingxia & Ibrahim, Joseph G. & Chen, Ming-Hui & Senchaudhuri, Pralay, 2008.
"Theory and inference for regression models with missing responses and covariates ,"
Journal of Multivariate Analysis ,
Elsevier, vol. 99(6), pages 1302-1331, July.
[Downloadable!] (restricted)
Herring A. H & Ibrahim J. G, 2001.
"Likelihood-Based Methods for Missing Covariates in the Cox Proportional Hazards Model ,"
Journal of the American Statistical Association ,
American Statistical Association, vol. 96, pages 292-302, March.
[Downloadable!] (restricted)
Jane Xu & Scott L. Zeger, 2001.
"Joint analysis of longitudinal data comprising repeated measures and times to events ,"
Journal Of The Royal Statistical Society Series C ,
Royal Statistical Society, vol. 50(3), pages 375-387.
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This page was last updated on 2009-11-27.
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