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Title: An Empirical Likelihood Approach to Reduce Selection Bias in Voluntary Samples
How to construct the pseudo-weights in voluntary samples is an important practical problem in survey sampling. The problem is quite challenging when the sampling mechanism for the voluntary sample is allowed to be non-ignorable. Under the assumption that the sample participation model is correctly specified, we can compute a consistent estimator of the model parameter and construct the propensity score estimator of the population mean. We propose using the empirical likelihood method to construct the final weights for voluntary samples by incorporating the bias calibration constraints and the benchmarking constraints. Linearization variance estimation of the proposed method is developed. A toy example is also presented to illustrate the idea and the computational details. A limited simulation study is also performed to evaluate the performance of the proposed methods.  more » « less
Award ID(s):
1931380
PAR ID:
10491976
Author(s) / Creator(s):
;
Publisher / Repository:
Sage Journals
Date Published:
Journal Name:
Calcutta Statistical Association Bulletin
Volume:
75
Issue:
1
ISSN:
0008-0683
Page Range / eLocation ID:
8 to 27
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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