We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham Research Online
You are in:

Estimation of small area total with randomized data.

Ahmed, S. and Shabbir, J. and Gupta, S. and Coolen, F.P.A. (2020) 'Estimation of small area total with randomized data.', REVSTAT - Statistical Journal., 18 (2). pp. 223-235.


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.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
File format - PDF
Full text:(VoR) Version of Record
Download PDF
Publisher Web site:
Date accepted:25 September 2019
Date deposited:08 October 2019
Date of first online publication:30 April 2020
Date first made open access:03 June 2020

Save or Share this output

Look up in GoogleScholar