Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data
In this paper, we present an estimation approach based on generalized estimating equations and a variable selection procedure for single-index models when the observed data are clustered. Unlike the case of independent observations, bias-correction is necessary when general working correlation matri...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2013
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| Online Access: | https://hdl.handle.net/10356/98050 http://hdl.handle.net/10220/17499 |
| _version_ | 1826110575895117824 |
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| author | Lai, Peng Wang, Qihua Lian, Heng |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Lai, Peng Wang, Qihua Lian, Heng |
| author_sort | Lai, Peng |
| collection | NTU |
| description | In this paper, we present an estimation approach based on generalized estimating equations and a variable selection procedure for single-index models when the observed data are clustered. Unlike the case of independent observations, bias-correction is necessary when general working correlation matrices are used in the estimating equations. Our variable selection procedure based on smooth-threshold estimating equations (Ueki (2009) [23]) can automatically eliminate irrelevant parameters by setting them as zeros and is computationally simpler than alternative approaches based on shrinkage penalty. The resulting estimator consistently identifies the significant variables in the index, even when the working correlation matrix is misspecified. The asymptotic property of the estimator is the same whether or not the nonzero parameters are known (in both cases we use the same estimating equations), thus achieving the oracle property in the sense of Fan and Li (2001) [10]. The finite sample properties of the estimator are illustrated by some simulation examples, as well as a real data application. |
| first_indexed | 2024-10-01T02:36:43Z |
| format | Journal Article |
| id | ntu-10356/98050 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:36:43Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/980502020-03-07T12:34:43Z Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data Lai, Peng Wang, Qihua Lian, Heng School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Analysis In this paper, we present an estimation approach based on generalized estimating equations and a variable selection procedure for single-index models when the observed data are clustered. Unlike the case of independent observations, bias-correction is necessary when general working correlation matrices are used in the estimating equations. Our variable selection procedure based on smooth-threshold estimating equations (Ueki (2009) [23]) can automatically eliminate irrelevant parameters by setting them as zeros and is computationally simpler than alternative approaches based on shrinkage penalty. The resulting estimator consistently identifies the significant variables in the index, even when the working correlation matrix is misspecified. The asymptotic property of the estimator is the same whether or not the nonzero parameters are known (in both cases we use the same estimating equations), thus achieving the oracle property in the sense of Fan and Li (2001) [10]. The finite sample properties of the estimator are illustrated by some simulation examples, as well as a real data application. 2013-11-08T06:51:01Z 2019-12-06T19:50:02Z 2013-11-08T06:51:01Z 2019-12-06T19:50:02Z 2011 2011 Journal Article Lai, P., Wang, Q., & Lian, H. (2011). Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data. Journal of multivariate analysis, 105(1), 422-432. 0047-259X https://hdl.handle.net/10356/98050 http://hdl.handle.net/10220/17499 10.1016/j.jmva.2011.08.009 en Journal of multivariate analysis |
| spellingShingle | DRNTU::Science::Mathematics::Analysis Lai, Peng Wang, Qihua Lian, Heng Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title | Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title_full | Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title_fullStr | Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title_full_unstemmed | Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title_short | Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data |
| title_sort | bias corrected gee estimation and smooth threshold gee variable selection for single index models with clustered data |
| topic | DRNTU::Science::Mathematics::Analysis |
| url | https://hdl.handle.net/10356/98050 http://hdl.handle.net/10220/17499 |
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