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On optional randomized response techniques in survey sampling
| Τίτλος: | On optional randomized response techniques in survey sampling |
|---|---|
| Συγγραφείς: | Pushadapu, Kavya |
| Στοιχεία εκδότη: | Texas A&M University-Kingsville |
| Έτος έκδοσης: | 2022 |
| Συλλογή: | Texas A&M University-Kingsville: AKM Digital Repository |
| Θεματικοί όροι: | Statistics, Sampling (Statistics) -- Computer programs, Modeling languages (Computer Science), Mathematics, Surveys, Statistical analytics, computing and modeling |
| Περιγραφή: | In this thesis, we considered the problem of estimation of proportion of a sensitive characteristic using a randomization device that allows interviewees to answer directly or indirectly to a sensitive question. This method is called an optional randomized response technique. An attempt is made to suggest an optimal optional randomized response estimator, for which the bias and variance expressions are derived, and the efficiency of the optimal estimator is investigated through simulation study using SAS coding. Additionally, the suggested approach is applied to COVID-19. In addition, we made a new optional randomized response technique for estimating prevalence of two sensitive characteristics and their overlap in a population. Estimators are proposed, and the variance expressions are derived, and estimators of variances are suggested, and analytical and empirical comparisons are investigated thoroughly. |
| Τύπος εγγράφου: | other/unknown material |
| Περιγραφή αρχείου: | pdf; 1,715,095 bytes |
| Γλώσσα: | English |
| Relation: | http://cdm16771.contentdm.oclc.org/u?/p16771coll2,1195 |
| Διαθεσιμότητα: | http://cdm16771.contentdm.oclc.org/u?/p16771coll2,1195 |
| Rights: | The right to download or print any of the pages of this thesis (Material) is granted by the copyright owner only for personal or classroom use. The author retains all proprietary rights, including copyright ownership. Any reproduction or editing or other use of this Material by any means requires the express written permission of the copyright owner. Except as provided above, or any use beyond what is allowed by fair use (Title 17 Section 107 U.S.C.), you may not reproduce, republish, post, transmit or distribute any Material from this web site in any physical or digital form without the permission of the copyright owner of the Material. Inquiries regarding any further use of these materials should be addressed to Administration, Jernigan Library, Texas A&M University-Kingsville, 700 University Blvd. Kingsville, Texas 78363-8202, (361)593-3416. |
| Αριθμός Καταχώρησης: | edsbas.F3549F17 |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: http://cdm16771.contentdm.oclc.org/u?/p16771coll2,1195# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Header | DbId: edsbas DbLabel: BASE An: edsbas.F3549F17 RelevancyScore: 842 AccessLevel: 3 PubType: Other/Unknown Material PubTypeId: unknown PreciseRelevancyScore: 842.276306152344 |
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| Items | – Name: Title Label: Title Group: Ti Data: On optional randomized response techniques in survey sampling – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pushadapu%2C+Kavya%22">Pushadapu, Kavya</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: Texas A&M University-Kingsville – Name: DatePubCY Label: Publication Year Group: Date Data: 2022 – Name: Subset Label: Collection Group: HoldingsInfo Data: Texas A&M University-Kingsville: AKM Digital Repository – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Sampling+%28Statistics%29+--+Computer+programs%22">Sampling (Statistics) -- Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Modeling+languages+%28Computer+Science%29%22">Modeling languages (Computer Science)</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics%22">Mathematics</searchLink><br /><searchLink fieldCode="DE" term="%22Surveys%22">Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+analytics%22">Statistical analytics</searchLink><br /><searchLink fieldCode="DE" term="%22computing+and+modeling%22">computing and modeling</searchLink> – Name: Abstract Label: Description Group: Ab Data: In this thesis, we considered the problem of estimation of proportion of a sensitive characteristic using a randomization device that allows interviewees to answer directly or indirectly to a sensitive question. This method is called an optional randomized response technique. An attempt is made to suggest an optimal optional randomized response estimator, for which the bias and variance expressions are derived, and the efficiency of the optimal estimator is investigated through simulation study using SAS coding. Additionally, the suggested approach is applied to COVID-19. In addition, we made a new optional randomized response technique for estimating prevalence of two sensitive characteristics and their overlap in a population. Estimators are proposed, and the variance expressions are derived, and estimators of variances are suggested, and analytical and empirical comparisons are investigated thoroughly. – Name: TypeDocument Label: Document Type Group: TypDoc Data: other/unknown material – Name: Format Label: File Description Group: SrcInfo Data: pdf; 1,715,095 bytes – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: http://cdm16771.contentdm.oclc.org/u?/p16771coll2,1195 – Name: URL Label: Availability Group: URL Data: http://cdm16771.contentdm.oclc.org/u?/p16771coll2,1195 – Name: Copyright Label: Rights Group: Cpyrght Data: The right to download or print any of the pages of this thesis (Material) is granted by the copyright owner only for personal or classroom use. The author retains all proprietary rights, including copyright ownership. Any reproduction or editing or other use of this Material by any means requires the express written permission of the copyright owner. Except as provided above, or any use beyond what is allowed by fair use (Title 17 Section 107 U.S.C.), you may not reproduce, republish, post, transmit or distribute any Material from this web site in any physical or digital form without the permission of the copyright owner of the Material. Inquiries regarding any further use of these materials should be addressed to Administration, Jernigan Library, Texas A&M University-Kingsville, 700 University Blvd. Kingsville, Texas 78363-8202, (361)593-3416. – Name: AN Label: Accession Number Group: ID Data: edsbas.F3549F17 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.F3549F17 |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: Statistics Type: general – SubjectFull: Sampling (Statistics) -- Computer programs Type: general – SubjectFull: Modeling languages (Computer Science) Type: general – SubjectFull: Mathematics Type: general – SubjectFull: Surveys Type: general – SubjectFull: Statistical analytics Type: general – SubjectFull: computing and modeling Type: general Titles: – TitleFull: On optional randomized response techniques in survey sampling Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pushadapu, Kavya IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
| ResultId | 1 |