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Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models

Studies with sensitive questions should include a sufficient number of respondents to adequately address the research interest. While studies with an inadequate number of respondents may not yield significant conclusions, studies with an excess of respondents become wasteful of investigators’ budget...

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Detalles Bibliográficos
Autores principales: Qiu, Shi-Fang, Tang, Man-Lai, Tao, Ji-Ran, Wong, Ricky S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636124/
https://www.ncbi.nlm.nih.gov/pubmed/35306631
http://dx.doi.org/10.1007/s11336-022-09854-w
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author Qiu, Shi-Fang
Tang, Man-Lai
Tao, Ji-Ran
Wong, Ricky S.
author_facet Qiu, Shi-Fang
Tang, Man-Lai
Tao, Ji-Ran
Wong, Ricky S.
author_sort Qiu, Shi-Fang
collection PubMed
description Studies with sensitive questions should include a sufficient number of respondents to adequately address the research interest. While studies with an inadequate number of respondents may not yield significant conclusions, studies with an excess of respondents become wasteful of investigators’ budget. Therefore, it is an important step in survey sampling to determine the required number of participants. In this article, we derive sample size formulas based on confidence interval estimation of prevalence for four randomized response models, namely, the Warner’s randomized response model, unrelated question model, item count technique model and cheater detection model. Specifically, our sample size formulas control, with a given assurance probability, the width of a confidence interval within the planned range. Simulation results demonstrate that all formulas are accurate in terms of empirical coverage probabilities and empirical assurance probabilities. All formulas are illustrated using a real-life application about the use of unethical tactics in negotiation.
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spelling pubmed-96361242022-11-06 Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models Qiu, Shi-Fang Tang, Man-Lai Tao, Ji-Ran Wong, Ricky S. Psychometrika Theory and Methods Studies with sensitive questions should include a sufficient number of respondents to adequately address the research interest. While studies with an inadequate number of respondents may not yield significant conclusions, studies with an excess of respondents become wasteful of investigators’ budget. Therefore, it is an important step in survey sampling to determine the required number of participants. In this article, we derive sample size formulas based on confidence interval estimation of prevalence for four randomized response models, namely, the Warner’s randomized response model, unrelated question model, item count technique model and cheater detection model. Specifically, our sample size formulas control, with a given assurance probability, the width of a confidence interval within the planned range. Simulation results demonstrate that all formulas are accurate in terms of empirical coverage probabilities and empirical assurance probabilities. All formulas are illustrated using a real-life application about the use of unethical tactics in negotiation. Springer US 2022-03-20 2022 /pmc/articles/PMC9636124/ /pubmed/35306631 http://dx.doi.org/10.1007/s11336-022-09854-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Theory and Methods
Qiu, Shi-Fang
Tang, Man-Lai
Tao, Ji-Ran
Wong, Ricky S.
Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title_full Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title_fullStr Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title_full_unstemmed Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title_short Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
title_sort sample size determination for interval estimation of the prevalence of a sensitive attribute under randomized response models
topic Theory and Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636124/
https://www.ncbi.nlm.nih.gov/pubmed/35306631
http://dx.doi.org/10.1007/s11336-022-09854-w
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