Please use this identifier to cite or link to this item:
https://doi.org/10.1002/cjs.10129
DC Field | Value | |
---|---|---|
dc.title | Improving variance function estimation in semiparametric longitudinal data analysis | |
dc.contributor.author | Leng, C. | |
dc.contributor.author | Tang, C.Y. | |
dc.date.accessioned | 2014-10-28T05:12:40Z | |
dc.date.available | 2014-10-28T05:12:40Z | |
dc.date.issued | 2011-12 | |
dc.identifier.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 | |
dc.identifier.issn | 03195724 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/105178 | |
dc.description.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. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/cjs.10129 | |
dc.source | Scopus | |
dc.subject | Asymptotic relative efficiency | |
dc.subject | Local linear estimator | |
dc.subject | Longitudinal data analysis | |
dc.subject | Variance function estimation | |
dc.type | Article | |
dc.contributor.department | STATISTICS & APPLIED PROBABILITY | |
dc.description.doi | 10.1002/cjs.10129 | |
dc.description.sourcetitle | Canadian Journal of Statistics | |
dc.description.volume | 39 | |
dc.description.issue | 4 | |
dc.description.page | 656-670 | |
dc.identifier.isiut | 000297112900006 | |
Appears in Collections: | Staff Publications |
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