Campus Units

Statistics

Document Type

Article

Publication Version

Published Version

Publication Date

2018

Journal or Book Title

Statistics and Applications

Volume

16

Issue

1

First Page

227

Last Page

243

Abstract

Combining information from several surveys, or survey integration, is an important practical problem in survey sampling. When the samples are selected from similar but different populations, random effect models can be used to describe the sample observations and to borrow strength from multiple surveys. In this paper, we consider a prediction approach to survey integration assuming random effect models. The sampling designs are allowed to be informative. The model parameters are estimated using a version of EM algorithm accounting for the sampling design. The mean squared error estimation is also discussed. Two limited simulation studies are used to investigate the performance of the proposed method.

Comments

This article is published as E. Gwak, J.K. Kim, and Y. Kim (2018). “A Random Effect Model Approach to Survey Data Integration," Statistics and Applications 16, 227-243. Posted with permission.

Copyright Owner

Society of Statistics, Computer and Applications

Language

en

File Format

application/pdf

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