Skip Navigation


Biostatistics Advance Access originally published online on July 14, 2005
Biostatistics 2006 7(1):115-129; doi:10.1093/biostatistics/kxi044
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Supplementary data
Right arrow All Versions of this Article:
7/1/115    most recent
kxi044v1
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 Similar articles in PubMed
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
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Ogden, R. T.
Right arrow Articles by Tarpey, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ogden, R. T.
Right arrow Articles by Tarpey, T.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oupjournals.org.

Estimation in regression models with externally estimated parameters

R. Todd Ogden*

Department of Biostatistics, Columbia University, 6th floor, 722 West 168th Street, New York, NY 10032, USA to166{at}columbia.edu

Thaddeus Tarpey

Department of Mathematics and Statistics, Wright State University, Dayton, OH 45435, USA

* To whom correspondence should be addressed.

In many regression applications, some of the model parameters are estimated from separate data sources. Typically, these estimates are plugged into the regression model and the remainder of the parameters is estimated from the primary data source. This situation arises frequently in compartment modeling when there is an external input function to the system. This paper provides asymptotic and bootstrap-based approaches for accounting for all sources of variability when computing standard errors for estimated regression model parameters. Examples and simulations are provided to motivate and illustrate the ideas.

Keywords: Bootstrap; Compartment models; PET imaging


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
 Am. J. Clin. Nutr.Home page
F. Imamura, P. F Jacques, D. M Herrington, G. E Dallal, and A. H Lichtenstein
Adherence to 2005 Dietary Guidelines for Americans is associated with a reduced progression of coronary artery atherosclerosis in women with established coronary artery disease
Am. J. Clinical Nutrition, July 1, 2009; 90(1): 193 - 201.
[Abstract] [Full Text] [PDF]

Home page
 JNMHome page
M. S. Milak, A. J. Severance, R. T. Ogden, J. Prabhakaran, J.S. D. Kumar, V. J. Majo, J. J. Mann, and R. V. Parsey
Modeling Considerations for 11C-CUMI-101, an Agonist Radiotracer for Imaging Serotonin 1A Receptor In Vivo with PET
J. Nucl. Med., April 1, 2008; 49(4): 587 - 596.
[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.