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OLS Field Name OLS Field Data
Main Title Unified methods for censored longitudinal data and causality /
Author Laan, M. J. van der.
Other Authors
Author Title of a Work
Robins, James M.
Publisher Springer,
Year Published 2003
OCLC Number 50280137
ISBN 0387955569; 9780387955568; 1441930558; 9781441930552
Subjects Nonparametric statistics. ; Censored observations (Statistics) ; Longitudinal method. ; Estimation theory. ; Statistiek. ; Longitudinaal onderzoek. ; Datenanalyse.--(DE-588)4123037-1 ; Längsschnittuntersuchung.--(DE-588)4034036-3 ; Schätzung.--(DE-588)4193791-0 ; Semiparametrisches Modell.--(DE-588)4232479-8 ; Análise de dados longitudinais (pesquisa ; planejamento) ; Statistique non paramétrique. ; Méthode longitudinale. ; Estimation, Théorie de l'. ; Statistique non param etrique ; M ethode longitudinale ; Estimation, Th eorie de l'
Internet Access
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MyiLibrary http://www.myilibrary.com?id=18955
Table of contents http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=009942583&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Table of contents http://swbplus.bsz-bw.de/bsz104060972inh.htm
Table of contents http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009942583&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Publisher description http://catdir.loc.gov/catdir/enhancements/fy0817/2002030239-d.html
Vorwort http://swbplus.bsz-bw.de/bsz104060972vor.htm
Vorwort http://swbplus.bsz-bw.de/bsz104060972vor.pdf
Kapitel 1 http://swbplus.bsz-bw.de/bsz104060972kap.htm
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EKBM  QA278.8.L33 2003 Research Triangle Park Library/RTP, NC 04/02/2004
Collation xii, 397 pages : illustrations ; 24 cm.
Notes
Includes bibliographical references (pages 371-387) and indexes.
Contents Notes
"This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so-called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph. D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data."--Jacket.