Skip Navigation

Biometrika 2006 93(3):627-640; doi:10.1093/biomet/93.3.627
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 Zeng, D.
Right arrow Articles by Lin, D. Y.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2006 Biometrika Trust

Efficient estimation of semiparametric transformation models for counting processes

Donglin Zeng and D. Y. Lin

Department of Biostatistics, CB# 7420, University of North Carolina, Chapel Hill, North Carolina 27599-7420, U.S.A. dzeng{at}bios.unc.edu, lin{at}bios.unc.edu

A class of semiparametric transformation models is proposed to characterise the effects of possibly time-varying covariates on the intensity functions of counting processes. The class includes the proportional intensity model and linear transformation models as special cases. Nonparametric maximum likelihood estimators are developed for the regression parameters and cumulative intensity functions of these models based on censored data. The estimators are shown to be consistent and asymptotically normal. The limiting variances for the estimators of the regression parameters achieve the semi-parametric efficient bounds and can be consistently estimated. The limiting variances for the estimators of smooth functionals of the cumulative intensity function can also be consistently estimated. Simulation studies reveal that the proposed inference procedures perform well in practical settings. Two medical studies are provided.

Key Words: Censoring; Intensity; Linear transformation model; Nonparametric likelihood; Proportional hazards; Proportional odds; Recurrent events; Semiparametric efficiency; Survival data; Time-varying covariate.

Received July 2004. Revised December 2005.


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




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.