File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1002/sim.1581
- Scopus: eid_2-s2.0-0345329164
- PMID: 14652867
- WOS: WOS:000186792500007
- Find via
Supplementary
-
Bookmarks:
- CiteULike: 1
- Citations:
- Appears in Collections:
Article: Median regression for longitudinal data
Title | Median regression for longitudinal data |
---|---|
Authors | |
Keywords | Efficiency Estimating equation Longitudinal data Median regression Mixed model Robustness |
Issue Date | 2003 |
Publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ |
Citation | Statistics in Medicine, 2003, v. 22 n. 23, p. 3655-3669 How to Cite? |
Abstract | We review and compare three estimators of median regression in linear models with longitudinal data. The estimators are constructed based on well-known ideas of weighting, decorrelating, and the working assumption of independence. Both asymptotic efficiency calculations and finite-sample Monte Carlo studies are used to assess the performance of these estimators. We find that their relative performances depend on the nature of covariates. The estimator under the working assumption of independence is computationally simple and yet has good relative performance when the covariates are invariant over time or when the within-subject correlations are small. Its relative performance in finite samples is also found to be more favourable than suggested by the asymptotic comparisons. Copyright © 2003 John Wiley & Sons, Ltd. |
Persistent Identifier | http://hdl.handle.net/10722/172407 |
ISSN | 2023 Impact Factor: 1.8 2023 SCImago Journal Rankings: 1.348 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | He, X | en_US |
dc.contributor.author | Fu, B | en_US |
dc.contributor.author | Fung, WK | en_US |
dc.date.accessioned | 2012-10-30T06:22:22Z | - |
dc.date.available | 2012-10-30T06:22:22Z | - |
dc.date.issued | 2003 | en_US |
dc.identifier.citation | Statistics in Medicine, 2003, v. 22 n. 23, p. 3655-3669 | en_US |
dc.identifier.issn | 0277-6715 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/172407 | - |
dc.description.abstract | We review and compare three estimators of median regression in linear models with longitudinal data. The estimators are constructed based on well-known ideas of weighting, decorrelating, and the working assumption of independence. Both asymptotic efficiency calculations and finite-sample Monte Carlo studies are used to assess the performance of these estimators. We find that their relative performances depend on the nature of covariates. The estimator under the working assumption of independence is computationally simple and yet has good relative performance when the covariates are invariant over time or when the within-subject correlations are small. Its relative performance in finite samples is also found to be more favourable than suggested by the asymptotic comparisons. Copyright © 2003 John Wiley & Sons, Ltd. | en_US |
dc.language | eng | en_US |
dc.publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ | en_US |
dc.relation.ispartof | Statistics in Medicine | en_US |
dc.rights | Statistics in Medicine. Copyright © John Wiley & Sons Ltd. | - |
dc.subject | Efficiency | - |
dc.subject | Estimating equation | - |
dc.subject | Longitudinal data | - |
dc.subject | Median regression | - |
dc.subject | Mixed model | - |
dc.subject | Robustness | - |
dc.subject.mesh | Analgesics - Pharmacology - Therapeutic Use | en_US |
dc.subject.mesh | Female | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | Labor, Obstetric - Physiology | en_US |
dc.subject.mesh | Linear Models | en_US |
dc.subject.mesh | Longitudinal Studies | en_US |
dc.subject.mesh | Pain - Drug Therapy | en_US |
dc.subject.mesh | Pregnancy | en_US |
dc.subject.mesh | Weight Lifting - Physiology | en_US |
dc.title | Median regression for longitudinal data | en_US |
dc.type | Article | en_US |
dc.identifier.email | Fung, WK: wingfung@hku.hk | en_US |
dc.identifier.authority | Fung, WK=rp00696 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1002/sim.1581 | en_US |
dc.identifier.pmid | 14652867 | - |
dc.identifier.scopus | eid_2-s2.0-0345329164 | en_US |
dc.identifier.hkuros | 90699 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0345329164&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 22 | en_US |
dc.identifier.issue | 23 | en_US |
dc.identifier.spage | 3655 | en_US |
dc.identifier.epage | 3669 | en_US |
dc.identifier.isi | WOS:000186792500007 | - |
dc.publisher.place | United Kingdom | en_US |
dc.identifier.scopusauthorid | He, X=7404407842 | en_US |
dc.identifier.scopusauthorid | Fu, B=35957954300 | en_US |
dc.identifier.scopusauthorid | Fung, WK=13310399400 | en_US |
dc.identifier.citeulike | 7688653 | - |
dc.identifier.issnl | 0277-6715 | - |