Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

A balanced multi-level rotation sampling design and its efficient composite estimators

Authors
Park, Y. S.Choi, J. W.Kim, K. W.
Issue Date
1-2월-2007
Publisher
ELSEVIER SCIENCE BV
Keywords
three-way balancing; minimurn risk estimator; generalized regression estimator; time-in-sample bias; recall bias
Citation
JOURNAL OF STATISTICAL PLANNING AND INFERENCE, v.137, no.2, pp.594 - 610
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume
137
Number
2
Start Page
594
End Page
610
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/125816
DOI
10.1016/j.jspi.2005.12.007
ISSN
0378-3758
Abstract
We present a multi-level rotation sampling design which includes most of the existing rotation designs as special cases. When an estimator is defined under this sampling design, its variance and bias remain the same over survey months, but it is not so under other existing rotation designs. Using the properties of this multi-level rotation design, we derive the mean squared error (MSE) of the generalized composite estimator (GCE), incorporating the two types of correlations arising from rotating sample units. We show that the MSEs of other existing composite estimators currently used can be expressed as special cases of the GCE. Furthermore, since the coefficients of the GCE are unknown and difficult to determine, we present the minimum risk window estimator (MRWE) as an alternative estimator. This MRWE has the smallest MSE under this rotation design and yet, it is easy to calculate. The MRWE is unbiased for monthly and yearly changes and preserves the internal consistency in total. Out-numerical study shows that the MRWE is as efficient as GCE and more efficient than the existing composite estimators and does not suffer from the drift problem [Fuller W.A., Rao J.N.K., 2001. A regression composite estimator with application to the Canadian Labour Force Survey. Surv. Methodol. 27 (2001) 45-51] unlike the regression composite estimators. (c) 2006 Elsevier B.V. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Political Science & Economics > Department of Statistics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE