Unbiased estimator modeling in unrelated dichotomous randomized response

The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased e...
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Gespeichert in:

Autor*in:	Adediran, Adetola Adedamola [verfasserIn] Adebola, Femi Barnabas [verfasserIn] Ewemooje, Olusegun Sunday [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Rechteinformationen:	Open Access Namensnennung 4.0 International ; CC BY 4.0

Schlagwörter:	dichotomous relative efficiency sensitive attribute

Übergeordnetes Werk:	Enthalten in: Statistics in transition - Warszawa : GUS, 2000, 21(2020), 5 vom: Dez., Seite 119-132
Übergeordnetes Werk:	volume:21 ; year:2020 ; number:5 ; month:12 ; pages:119-132

Links:	Link aufrufen Link aufrufen Link aufrufen

DOI / URN:	10.21307/stattrans-2020-058

Katalog-ID:	1776202821

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allfields	10.21307/stattrans-2020-058 doi 10419/236808 hdl (DE-627)1776202821 (DE-599)KXP1776202821 DE-627 ger DE-627 rda eng Adediran, Adetola Adedamola verfasserin (DE-588)1248063376 (DE-627)1782588264 aut Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206 Adebola, Femi Barnabas verfasserin (DE-588)1248063937 (DE-627)1782588876 aut Ewemooje, Olusegun Sunday verfasserin (DE-588)1248064992 (DE-627)1782589872 aut Enthalten in Statistics in transition Warszawa : GUS, 2000 21(2020), 5 vom: Dez., Seite 119-132 Online-Ressource (DE-627)512298068 (DE-600)2235641-1 (DE-576)281309450 2450-0291 nnns volume:21 year:2020 number:5 month:12 pages:119-132 https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 Verlag kostenfrei https://doi.org/10.21307/stattrans-2020-058 Resolving-System kostenfrei http://hdl.handle.net/10419/236808 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2863 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 21 2020 5 12 119-132 26 01 0206 3999130482 x1z 04-11-21 2403 01 DE-LFER 4001555069 00 --%%-- --%%-- n --%%-- l01 11-11-21 2403 01 DE-LFER https://doi.org/10.21307/stattrans-2020-058 2403 01 DE-LFER https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058
spelling	10.21307/stattrans-2020-058 doi 10419/236808 hdl (DE-627)1776202821 (DE-599)KXP1776202821 DE-627 ger DE-627 rda eng Adediran, Adetola Adedamola verfasserin (DE-588)1248063376 (DE-627)1782588264 aut Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206 Adebola, Femi Barnabas verfasserin (DE-588)1248063937 (DE-627)1782588876 aut Ewemooje, Olusegun Sunday verfasserin (DE-588)1248064992 (DE-627)1782589872 aut Enthalten in Statistics in transition Warszawa : GUS, 2000 21(2020), 5 vom: Dez., Seite 119-132 Online-Ressource (DE-627)512298068 (DE-600)2235641-1 (DE-576)281309450 2450-0291 nnns volume:21 year:2020 number:5 month:12 pages:119-132 https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 Verlag kostenfrei https://doi.org/10.21307/stattrans-2020-058 Resolving-System kostenfrei http://hdl.handle.net/10419/236808 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2863 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 21 2020 5 12 119-132 26 01 0206 3999130482 x1z 04-11-21 2403 01 DE-LFER 4001555069 00 --%%-- --%%-- n --%%-- l01 11-11-21 2403 01 DE-LFER https://doi.org/10.21307/stattrans-2020-058 2403 01 DE-LFER https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058
allfields_unstemmed	10.21307/stattrans-2020-058 doi 10419/236808 hdl (DE-627)1776202821 (DE-599)KXP1776202821 DE-627 ger DE-627 rda eng Adediran, Adetola Adedamola verfasserin (DE-588)1248063376 (DE-627)1782588264 aut Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206 Adebola, Femi Barnabas verfasserin (DE-588)1248063937 (DE-627)1782588876 aut Ewemooje, Olusegun Sunday verfasserin (DE-588)1248064992 (DE-627)1782589872 aut Enthalten in Statistics in transition Warszawa : GUS, 2000 21(2020), 5 vom: Dez., Seite 119-132 Online-Ressource (DE-627)512298068 (DE-600)2235641-1 (DE-576)281309450 2450-0291 nnns volume:21 year:2020 number:5 month:12 pages:119-132 https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 Verlag kostenfrei https://doi.org/10.21307/stattrans-2020-058 Resolving-System kostenfrei http://hdl.handle.net/10419/236808 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2863 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 21 2020 5 12 119-132 26 01 0206 3999130482 x1z 04-11-21 2403 01 DE-LFER 4001555069 00 --%%-- --%%-- n --%%-- l01 11-11-21 2403 01 DE-LFER https://doi.org/10.21307/stattrans-2020-058 2403 01 DE-LFER https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058
allfieldsGer	10.21307/stattrans-2020-058 doi 10419/236808 hdl (DE-627)1776202821 (DE-599)KXP1776202821 DE-627 ger DE-627 rda eng Adediran, Adetola Adedamola verfasserin (DE-588)1248063376 (DE-627)1782588264 aut Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206 Adebola, Femi Barnabas verfasserin (DE-588)1248063937 (DE-627)1782588876 aut Ewemooje, Olusegun Sunday verfasserin (DE-588)1248064992 (DE-627)1782589872 aut Enthalten in Statistics in transition Warszawa : GUS, 2000 21(2020), 5 vom: Dez., Seite 119-132 Online-Ressource (DE-627)512298068 (DE-600)2235641-1 (DE-576)281309450 2450-0291 nnns volume:21 year:2020 number:5 month:12 pages:119-132 https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 Verlag kostenfrei https://doi.org/10.21307/stattrans-2020-058 Resolving-System kostenfrei http://hdl.handle.net/10419/236808 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2863 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 21 2020 5 12 119-132 26 01 0206 3999130482 x1z 04-11-21 2403 01 DE-LFER 4001555069 00 --%%-- --%%-- n --%%-- l01 11-11-21 2403 01 DE-LFER https://doi.org/10.21307/stattrans-2020-058 2403 01 DE-LFER https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058
allfieldsSound	10.21307/stattrans-2020-058 doi 10419/236808 hdl (DE-627)1776202821 (DE-599)KXP1776202821 DE-627 ger DE-627 rda eng Adediran, Adetola Adedamola verfasserin (DE-588)1248063376 (DE-627)1782588264 aut Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206 Adebola, Femi Barnabas verfasserin (DE-588)1248063937 (DE-627)1782588876 aut Ewemooje, Olusegun Sunday verfasserin (DE-588)1248064992 (DE-627)1782589872 aut Enthalten in Statistics in transition Warszawa : GUS, 2000 21(2020), 5 vom: Dez., Seite 119-132 Online-Ressource (DE-627)512298068 (DE-600)2235641-1 (DE-576)281309450 2450-0291 nnns volume:21 year:2020 number:5 month:12 pages:119-132 https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 Verlag kostenfrei https://doi.org/10.21307/stattrans-2020-058 Resolving-System kostenfrei http://hdl.handle.net/10419/236808 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2863 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 21 2020 5 12 119-132 26 01 0206 3999130482 x1z 04-11-21 2403 01 DE-LFER 4001555069 00 --%%-- --%%-- n --%%-- l01 11-11-21 2403 01 DE-LFER https://doi.org/10.21307/stattrans-2020-058 2403 01 DE-LFER https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058
language	English
source	Enthalten in Statistics in transition 21(2020), 5 vom: Dez., Seite 119-132 volume:21 year:2020 number:5 month:12 pages:119-132
sourceStr	Enthalten in Statistics in transition 21(2020), 5 vom: Dez., Seite 119-132 volume:21 year:2020 number:5 month:12 pages:119-132
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institution	findex.gbv.de
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topic_facet	dichotomous relative efficiency sensitive attribute
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container_title	Statistics in transition
authorswithroles_txt_mv	Adediran, Adetola Adedamola @@aut@@ Adebola, Femi Barnabas @@aut@@ Ewemooje, Olusegun Sunday @@aut@@
publishDateDaySort_date	2020-12-01T00:00:00Z
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topic_title	Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje dichotomous (dpeaa)DE-206 relative efficiency (dpeaa)DE-206 sensitive attribute (dpeaa)DE-206
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title	Unbiased estimator modeling in unrelated dichotomous randomized response
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title_full	Unbiased estimator modeling in unrelated dichotomous randomized response Adetola Adedamola Adediran, Femi Barnabas Adebola, Olusegun Sunday Ewemooje
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title_sort	unbiased estimator modeling in unrelated dichotomous randomized response
title_auth	Unbiased estimator modeling in unrelated dichotomous randomized response
abstract	The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases.
abstractGer	The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases.
abstract_unstemmed	The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students; the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases.
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title_short	Unbiased estimator modeling in unrelated dichotomous randomized response
url	https://www.exeley.com/statistics_in_transition/pdf/10.21307/stattrans-2020-058 https://doi.org/10.21307/stattrans-2020-058 http://hdl.handle.net/10419/236808
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Unbiased estimator modeling in unrelated dichotomous randomized response

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