Skip Navigation

Biometrika 2009 96(2):383-398; doi:10.1093/biomet/asp015
This Article
Right arrow Full Text (PDF)
Right arrow References
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 Carroll, R. J.
Right arrow Articles by Yu, K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2009 Biometrika Trust

Article

Nonparametric additive regression for repeatedly measured data

Raymond J. Carroll

Department of Statistics, Texas A&M University, College Station, Texas 77843, U.S.A. carroll{at}stat.tamu.edu

Arnab Maity

Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, Massachusetts 02115, U.S.A. amaity{at}hsph.harvard.edu

Enno Mammen and Kyusang Yu

Department of Economics, University of Mannheim, L 7, 3-5, 68131 Mannheim, Germany emammen{at}rumms.uni-mannheim.de kyusangu{at}yahoo.co.kr

Received for publication 1 October 2007. Revision received 1 October 2008.
  Abstract

We develop an easily computed smooth backfitting algorithm for additive model fitting in repeated measures problems. Our methodology easily copes with various settings, such as when some covariates are the same over repeated response measurements. We allow for a working covariance matrix for the regression errors, showing that our method is most efficient when the correct covariance matrix is used. The component functions achieve the known asymptotic variance lower bound for the scalar argument case. Smooth backfitting also leads directly to design-independent biases in the local linear case. Simulations show our estimator has smaller variance than the usual kernel estimator. This is also illustrated by an example from nutritional epidemiology.

Key Words: Additive model • Generalized least square • Nonparametric regression • Repeated measure • Smooth backfitting


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.