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Population-level information for improving quantile regression efficiency.
- Source :
-
Statistics & Probability Letters . Dec2024, Vol. 215, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Observational studies often rely on sample survey data for estimation, given the difficulty of obtaining exhaustive information for the entire population. However, the use of sample data can lead to a reduction in estimation efficiency due to sampling error. When certain population-level data are accessible, devising an effective strategy to integrate them into the underlying estimation process proves advantageous. This paper proposes a methodology based on empirical likelihood for conducting quantile regression analysis on longitudinal data while incorporating population-level information. Both theoretical analysis and numerical simulations demonstrate that the proposed approach outperforms estimation methods that do not leverage population-level data. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01677152
- Volume :
- 215
- Database :
- Academic Search Index
- Journal :
- Statistics & Probability Letters
- Publication Type :
- Periodical
- Accession number :
- 179420746
- Full Text :
- https://doi.org/10.1016/j.spl.2024.110227