The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Penalized Functional Regression
Open accessAbstract
We develop fast fitting methods for generalized functional linear models. The functional predictor is projected onto a large number of smooth eigenvectors and the coefficient function is estimated using penalized spline regression; confidence intervals based on the mixed model framework are obtained. Our method can be applied to many functional data designs including functions measured with and without error, sparsely or densely sampled. The methods also extend to the case of multiple functional predictors or functional predictors with a natural multilevel structure. The approach can be implemented using standard mixed effects software and is computationally fast. The methodology is motivated by a study of white-matter demyelination via diffusion tensor imaging (DTI). The aim of this study is to analyze differences between various cerebral white-matter tract property measurements of multiple sclerosis (MS) patients and controls. While the statistical developments proposed here were motivated by the DTI study, the methodology is designed and presented in generality and is applicable to many other areas of scientific research. An online appendix provides R implementations of all simulations.
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Cites
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
nlme : Linear and nonlinear mixed effects models
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MR diffusion tensor spectroscopy and imaging
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Diffusion tensor imaging: Concepts and applications
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Selecting the Number of Knots for Penalized Splines
Ruppert, D. (2002) · Journal of Computational and Graphical Statistics · doi:10.1198/106186002321018768 · Cited by 709
Generalized functional linear models
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Applied Functional Data Analysis
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Cited by
Ben-Zeev, D., Scherer, E. A., Wang, R., Xie, H., & Campbell, A. T. (2015) · Psychiatric Rehabilitation Journal · doi:10.1037/prj0000130 · Cited by 429
Morris, J. S. (2015) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-010814-020413 · Cited by 423
Naslund, J. A., Aschbrenner, K. A., Scherer, E. A., McHugo, G. J., Marsch, L. A., & Bartels, S. J. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.06.056 · Cited by 86
Metadata
- Authors
- Goldsmith, J., Bobb, J., Crainiceanu, C. M., Caffo, B., & Reich, D.
- Venue
- Journal of Computational and Graphical Statistics
- Publisher
- Informa UK Limited
- Published
- 2011-01
- Volume
- 20
- Issue
- 4
- Pages
- 830-851
- ISSN
- 1061-8600 (ISSN-L)
- 1537-2715
- OpenAlex
- W2027515083
- Cited by
- 288
- References
- 24
- FWCI
- 12.80
- Type
- journal article
- Language
- en
- Open access
- green
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