Please use this identifier to cite or link to this item: https://doi.org/10.1002/cjs.10129
Title: Improving variance function estimation in semiparametric longitudinal data analysis
Authors: Leng, C. 
Tang, C.Y. 
Keywords: Asymptotic relative efficiency
Local linear estimator
Longitudinal data analysis
Variance function estimation
Issue Date: Dec-2011
Citation: Leng, C., Tang, C.Y. (2011-12). Improving variance function estimation in semiparametric longitudinal data analysis. Canadian Journal of Statistics 39 (4) : 656-670. ScholarBank@NUS Repository. https://doi.org/10.1002/cjs.10129
Abstract: We propose an efficient and robust method for variance function estimation in semiparametric longitudinal data analysis. The method utilizes a local log-linear approximation for the variance function and adopts a generalized estimating equation approach to account for within subject correlations. We show theoretically and empirically that our method outperforms estimators using working independence that ignores the correlations. © 2011 Statistical Society of Canada.
Source Title: Canadian Journal of Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/105178
ISSN: 03195724
DOI: 10.1002/cjs.10129
Appears in Collections:Staff Publications

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