Skip Navigation

Biometrika 1999 86(4):755-764; doi:10.1093/biomet/86.4.755
© 1999 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Chen, K
Right arrow Articles by Lo, S-H
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Case-cohort and case-control analysis with Cox's model

K ChenA1 and S-H LoA

A1 Department of Mathematics, Hong Kong University of Science and Technology, Kowloon, Hong Kong, PRC E-mail: makchen@uxmail.ust.hk A Department of Statistics, Columbia University, New York, NY 10027, USA E-mail: slo@stat.columbia.edu

Prentice (1986) proposed the case-cohort design and studied a pseudolikelihood estimator of regression parameters in Cox's model. We derive a class of estimating equations for case-cohort sampling, each depending on a different estimator of the population distribution, which lead naturally to simple estimators that improve on Prentice's pseudolikelihood estimator. We also discuss an equivalence between case-control and case-cohort sampling in terms of the estimation of regression parameters in Cox's model.

Key Words: asymptotic variance; estimating equation; partial likelihood; proportional hazards model


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BiometrikaHome page
S. Kang and J. Cai
Marginal hazards model for case-cohort studies with multiple disease outcomes
Biometrika, December 1, 2009; 96(4): 887 - 901.
[Abstract] [PDF]

Home page
 Am J EpidemiolHome page
L. S. Freedman, B. Oberman, and S. Sadetzki
Using Time-dependent Covariate Analysis to Elucidate the Relation of Smoking History to Warthin's Tumor Risk
Am. J. Epidemiol., November 1, 2009; 170(9): 1178 - 1185.
[Abstract] [Full Text] [PDF]

Home page
 BiometrikaHome page
X. Luo, W. Y. Tsai, and Q. Xu
Pseudo-partial likelihood estimators for the Cox regression model with missing covariates
Biometrika, September 1, 2009; 96(3): 617 - 633.
[Abstract] [PDF]

Home page
 JCOHome page
S. S. Badve, F. L. Baehner, R. P. Gray, B. H. Childs, T. Maddala, M.-L. Liu, S. C. Rowley, S. Shak, E. D. Perez, L. J. Shulman, et al.
Estrogen- and Progesterone-Receptor Status in ECOG 2197: Comparison of Immunohistochemistry by Local and Central Laboratories and Quantitative Reverse Transcription Polymerase Chain Reaction by Central Laboratory
J. Clin. Oncol., May 20, 2008; 26(15): 2473 - 2481.
[Abstract] [Full Text] [PDF]

Home page
 Am J EpidemiolHome page
K. Leffondre, M. Abrahamowicz, J. Siemiatycki, and B. Rachet
Modeling Smoking History: A Comparison of Different Approaches
Am. J. Epidemiol., November 1, 2002; 156(9): 813 - 823.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.