Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/asr050
Title: Empirical likelihood and quantile regression in longitudinal data analysis
Authors: Tang, C.Y. 
Leng, C. 
Keywords: Auxiliary information
Empirical likelihood
Estimating equation
Longitudinal data analysis
Quadratic inference function
Quantile regression
Issue Date: Dec-2011
Citation: Tang, C.Y., Leng, C. (2011-12). Empirical likelihood and quantile regression in longitudinal data analysis. Biometrika 98 (4) : 1001-1006. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/asr050
Abstract: We propose a novel quantile regression approach for longitudinal data analysis which naturally incorporates auxiliary information from the conditional mean model to account for within-subject correlations. The efficiency gain is quantified theoretically and demonstrated empirically via simulation studies and the analysis of a real dataset. © 2011 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105114
ISSN: 00063444
DOI: 10.1093/biomet/asr050
Appears in Collections:Staff Publications

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