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- Title
Variable selection in rank regression for analyzing longitudinal data.
- Authors
Liya Fu; You-Gan Wang; Fu, Liya; Wang, You-Gan
- Abstract
In this paper, we consider variable selection in rank regression models for longitudinal data. To obtain both robustness and effective selection of important covariates, we propose incorporating shrinkage by adaptive lasso or SCAD in the Wilcoxon dispersion function and establishing the oracle properties of the new method. The new method can be conveniently implemented with the statistical software R. The performance of the proposed method is demonstrated via simulation studies. Finally, two datasets are analyzed for illustration. Some interesting findings are reported and discussed.
- Subjects
REGRESSION analysis; GENERALIZED estimating equations; SUPERVISORY control &; data acquisition systems; WILCOXON signed-rank test; DISPERSION (Chemistry); CELL cycle; COMPARATIVE studies; COMPUTER simulation; EXPERIMENTAL design; LONGITUDINAL method; RESEARCH methodology; MEDICAL cooperation; NONPARAMETRIC statistics; PROGESTERONE; RESEARCH; STATISTICS; YEAST; DATA analysis; EVALUATION research; STATISTICAL models
- Publication
Statistical Methods in Medical Research, 2018, Vol 27, Issue 8, p2447
- ISSN
0962-2802
- Publication type
journal article
- DOI
10.1177/0962280216681347