Campus Units

Statistics

Document Type

Article

Publication Version

Published Version

Publication Date

1-2009

Journal or Book Title

Statistica Sinica

Volume

19

Issue

1

First Page

145

Last Page

157

Abstract

Calibration estimation, which can be roughly described as adjusting the original design weights to incorporate the known population totals of the auxiliary variables, has become very popular in sample surveys.The calibration weights are chosen to minimize a given distance measure while satisfying a set of constraints related to the auxiliary variable information. Under simple random sampling, Chen and Qin (1993) suggested that the calibration estimator maximizing the constrained empirical likelihood can make efficient use of the auxiliary variables. We extend the result to unequal probability sampling and propose an algorithm to implement the proposed procedure. Asymptotic properties of the proposed calibration estimator are discussed. The proposed method is extended to the stratified sampling. Results from a limited simulation study are presented.

Comments

This is an article published as Kim, Jae Kwang. "Calibration estimation using empirical likelihood in survey sampling." Statistica Sinica (2009): 145-157. Posted with permission.

Copyright Owner

Institute of Statistical Science, Academia Sinica

Language

en

File Format

application/pdf