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Contributions to non-randomized response models / Eman Esam Fathallah Mohammad ; Supervised Reda Ibrahim Mazloum , Sally Farid Abdelfatah

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Eman Esam Fathallah Mohammad , 2021Description: 73 P . : charts ; 25cmOther title:
  • مساهمات فى نماذج الاستجابة الغير عشوائية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Science - Department of Statistics Summary: The Non-Randomized Response (NRR) technique is a procedure that can be used in surveys with sensitive questions. In this thesis, some of the existing NRR models are extended to stratified random sampling. Efficiency comparisons between the extended models are then carried out. Moreover, three new improved non-randomized response models are proposed. The first proposed model is the alternating parallel model which is built on relaxing one of the assumptions of the parallel model. The second model is the non-randomized version of Sayed and Mazloum (2020) model, and the third proposed model is the parallel model under non-compliance. Finally, the efficiency of the proposed models is discussed
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.03.01.M.Sc.2021.Em.C (Browse shelf(Opens below)) Not for loan 01010110085365000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.03.01.M.Sc.2021.Em.C (Browse shelf(Opens below)) 85365.CD Not for loan 01020110085365000

Thesis (M.Sc.) - Cairo University - Faculty of Science - Department of Statistics

The Non-Randomized Response (NRR) technique is a procedure that can be used in surveys with sensitive questions. In this thesis, some of the existing NRR models are extended to stratified random sampling. Efficiency comparisons between the extended models are then carried out. Moreover, three new improved non-randomized response models are proposed. The first proposed model is the alternating parallel model which is built on relaxing one of the assumptions of the parallel model. The second model is the non-randomized version of Sayed and Mazloum (2020) model, and the third proposed model is the parallel model under non-compliance. Finally, the efficiency of the proposed models is discussed

Issued also as CD

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