NONRANDOMIZED RESPONSE MODEL FOR COMPLEX SURVEY DESIGNS
Warner’s randomized response (RR) model is used to collect sensitive information for a broad range of surveys, but it possesses several limitations such as lack of reproducibility, higher costs and it is not feasible for mail questionnaires. To overcome such difficulties, nonrandomized response (NRR...
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Veröffentlicht in: | Statistics in Transition New Series 2019-03, Vol.20 (1), p.67-86 |
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creator | Arnab, Raghunath Shangodoyin, D. K Arcos, Antonio |
description | Warner’s randomized response (RR) model is used to collect sensitive information for a broad range of surveys, but it possesses several limitations such as lack of reproducibility, higher costs and it is not feasible for mail questionnaires. To overcome such difficulties, nonrandomized response (NRR) surveys have been proposed. The proposed NRR surveys are limited to simple random sampling with replacement (SRSWR) design. In this paper, NRR procedures are extended to complex survey designs in a unified setup, which is applicable to any sampling design and wider classes of estimators. Existing results for NRR can be derived from the proposed method as special cases. |
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K ; Arcos, Antonio</creator><creatorcontrib>Arnab, Raghunath ; Shangodoyin, D. K ; Arcos, Antonio</creatorcontrib><description>Warner’s randomized response (RR) model is used to collect sensitive information for a broad range of surveys, but it possesses several limitations such as lack of reproducibility, higher costs and it is not feasible for mail questionnaires. To overcome such difficulties, nonrandomized response (NRR) surveys have been proposed. The proposed NRR surveys are limited to simple random sampling with replacement (SRSWR) design. In this paper, NRR procedures are extended to complex survey designs in a unified setup, which is applicable to any sampling design and wider classes of estimators. Existing results for NRR can be derived from the proposed method as special cases.</description><identifier>ISSN: 1234-7655</identifier><identifier>ISSN: 2450-0291</identifier><identifier>EISSN: 2450-0291</identifier><identifier>DOI: 10.21307/stattrans-2019-004</identifier><language>eng</language><publisher>New York, NY: Statistics Poland</publisher><subject>62D05 ; complex survey designs ; Economy ; parallel model ; probability proportional to size ; randomized response ; varying probability sampling</subject><ispartof>Statistics in Transition New Series, 2019-03, Vol.20 (1), p.67-86</ispartof><rights>COPYRIGHT 2019 Exeley Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3487-1228edf7211677805ab0a3ccf343e8dac10c4bd3ce3294671c5ef1f062e030df3</citedby><cites>FETCH-LOGICAL-c3487-1228edf7211677805ab0a3ccf343e8dac10c4bd3ce3294671c5ef1f062e030df3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.ceeol.com//api/image/getissuecoverimage?id=picture_2019_48176.jpeg</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Arnab, Raghunath</creatorcontrib><creatorcontrib>Shangodoyin, D. K</creatorcontrib><creatorcontrib>Arcos, Antonio</creatorcontrib><title>NONRANDOMIZED RESPONSE MODEL FOR COMPLEX SURVEY DESIGNS</title><title>Statistics in Transition New Series</title><addtitle>Statistics in Transition New Series</addtitle><description>Warner’s randomized response (RR) model is used to collect sensitive information for a broad range of surveys, but it possesses several limitations such as lack of reproducibility, higher costs and it is not feasible for mail questionnaires. To overcome such difficulties, nonrandomized response (NRR) surveys have been proposed. The proposed NRR surveys are limited to simple random sampling with replacement (SRSWR) design. In this paper, NRR procedures are extended to complex survey designs in a unified setup, which is applicable to any sampling design and wider classes of estimators. Existing results for NRR can be derived from the proposed method as special cases.</description><subject>62D05</subject><subject>complex survey designs</subject><subject>Economy</subject><subject>parallel model</subject><subject>probability proportional to size</subject><subject>randomized response</subject><subject>varying probability sampling</subject><issn>1234-7655</issn><issn>2450-0291</issn><issn>2450-0291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>REL</sourceid><recordid>eNp9kFFPwjAUhRujiUT5BWqyPzC8bbd1e5PAQBLYCBOjvjSla8kIMNOOGP69nRB9M304TdPv3HsOQncYegRTYI-2EU1jxN76BHDiAwQXqEOCEHwgCb5EHUxo4LMoDK9R19oNAJCYBSyKO4hlebboZ8N8NvlIh94iLeZ5VqTeLB-mU2-UL7xBPptP0zevWC5e03dvmBaTcVbcoisttlZ1z3qDlqP0ZfDsT_PxZNCf-pIGMfMxIbEqNSMYR4zFEIoVCCqlpgFVcSkkBhmsSioVJUkQMSxDpbGGiCigUGp6g3on37XYKl7tde2SSndKtatkvVe6cu_9KGzzJJg5gJ4AaWprjdL801Q7YY4cA__pi__2xdu-uOvLUU8n6ktsG2VKtTaHo7vwTX0wexfwP9pp1A5-OFkot1ZleSu2qY37xhLSjrg_L6ZUvf0zZowlCaXf3hGEAw</recordid><startdate>20190301</startdate><enddate>20190301</enddate><creator>Arnab, Raghunath</creator><creator>Shangodoyin, D. 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K ; Arcos, Antonio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3487-1228edf7211677805ab0a3ccf343e8dac10c4bd3ce3294671c5ef1f062e030df3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>62D05</topic><topic>complex survey designs</topic><topic>Economy</topic><topic>parallel model</topic><topic>probability proportional to size</topic><topic>randomized response</topic><topic>varying probability sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Arnab, Raghunath</creatorcontrib><creatorcontrib>Shangodoyin, D. K</creatorcontrib><creatorcontrib>Arcos, Antonio</creatorcontrib><collection>Central and Eastern European Online Library (C.E.E.O.L.) 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subjects | 62D05 complex survey designs Economy parallel model probability proportional to size randomized response varying probability sampling |
title | NONRANDOMIZED RESPONSE MODEL FOR COMPLEX SURVEY DESIGNS |
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