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https://doi.org/10.1177/0962280208099447
DC Field | Value | |
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dc.title | Selection of covariance patterns for longitudinal data in semi-parametric models | |
dc.contributor.author | Li, J. | |
dc.contributor.author | Wong, W.K. | |
dc.date.accessioned | 2014-10-28T05:14:54Z | |
dc.date.available | 2014-10-28T05:14:54Z | |
dc.date.issued | 2010-04 | |
dc.identifier.citation | Li, J., Wong, W.K. (2010-04). Selection of covariance patterns for longitudinal data in semi-parametric models. Statistical Methods in Medical Research 19 (2) : 183-196. ScholarBank@NUS Repository. https://doi.org/10.1177/0962280208099447 | |
dc.identifier.issn | 09622802 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/105349 | |
dc.description.abstract | The use of patterned covariance structures in the parametric analysis of longitudinal data is both elegant and efficient. However, this strategy has not been well studied for semi-parametric models for analysing such data. We propose to estimate the covariance matrix in the semi-parametric model by rearranging the non-parametric component as a profiled linear function of the data and using a local smoothing technique. This results in a parametric regression formulation that enables us to construct likelihood functions and use various information criteria to select the best fitting covariance matrix. We apply our method to reanalyse data from a two-armed clinical trial for Scleroderma patients and show our method is more efficient for estimating the parametric components in the semi-parametric model. © 2010 The Author(s),Reprints and permissions. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1177/0962280208099447 | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | STATISTICS & APPLIED PROBABILITY | |
dc.description.doi | 10.1177/0962280208099447 | |
dc.description.sourcetitle | Statistical Methods in Medical Research | |
dc.description.volume | 19 | |
dc.description.issue | 2 | |
dc.description.page | 183-196 | |
dc.description.coden | SMMRF | |
dc.identifier.isiut | 000277010900005 | |
Appears in Collections: | Staff Publications |
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