Estimation of small area total with randomized data

Ahmed, S.; Shabbir, J.; Gupta, S.; Coolen, F.P.A.

Estimation of small area total with randomized data

Ahmed, S.; Shabbir, J.; Gupta, S.; Coolen, F.P.A.

Authors

S. Ahmed

J. Shabbir

S. Gupta

Professor Frank Coolen frank.coolen@durham.ac.uk
Professor

Abstract

In social surveys involving questions that are sensitive or personal in nature, respondents may not provide correct answers to certain questions asked by the interviewer. The impact of this nonresponse or inaccurate response becomes even more acute in the case of small area estimation (SAE) where we already have the problem of small sample size coming from the small area. To obtain a truthful response, we use randomized response techniques in each small area. We assume that a non-sensitive auxiliary variable, highly correlated with the study variable, is available. We use the word model in two senses — one in the context of population models, i.e. the relationship between the study variable and the auxiliary variable; and second, the scrambled response model. We focus on the problem of estimating small area total and examine its performance both theoretically and numerically.

Citation

Ahmed, S., Shabbir, J., Gupta, S., & Coolen, F. (2020). Estimation of small area total with randomized data. Revstat Statistical Journal, 18(2), 223-235

Journal Article Type	Article
Acceptance Date	Sep 25, 2019
Online Publication Date	Apr 30, 2020
Publication Date	Apr 30, 2020
Deposit Date	Oct 7, 2019
Publicly Available Date	Jun 3, 2020
Journal	Revstat Statistical Journal
Print ISSN	1645-6726
Publisher	Instituto Nacional de Estatística
Peer Reviewed	Peer Reviewed
Volume	18
Issue	2
Pages	223-235
Publisher URL	https://www.ine.pt/revstat/tables.html