Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error
This study explores the estimation of the mean of a sensitive variable using calibration estimators under measurement error. Three randomized response techniques are evaluated: Partial Randomized Response Technique, Compulsory Randomized Response Technique, and Optional Randomized Response Technique...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-08-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/15/2532 |
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| author | Sat Gupta Pidugu Trisandhya Frank Coolen |
| author_facet | Sat Gupta Pidugu Trisandhya Frank Coolen |
| author_sort | Sat Gupta |
| collection | DOAJ |
| description | This study explores the estimation of the mean of a sensitive variable using calibration estimators under measurement error. Three randomized response techniques are evaluated: Partial Randomized Response Technique, Compulsory Randomized Response Technique, and Optional Randomized Response Technique. Theoretical properties of the proposed estimators are analyzed, and a simulation study using real COVID-19 infection data is conducted. Results indicate that the Optional Randomized Response Technique outperforms Partial Randomized Response Technique and Compulsory Randomized Response Technique in terms of efficiency, underscoring its effectiveness and practical utility for improving data quality in sensitive survey settings. |
| format | Article |
| id | doaj-art-e6049b220025448d8d67ee4a4bb46c8e |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-e6049b220025448d8d67ee4a4bb46c8e2025-08-20T03:04:43ZengMDPI AGMathematics2227-73902025-08-011315253210.3390/math13152532Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement ErrorSat Gupta0Pidugu Trisandhya1Frank Coolen2Department of Mathematics and Statistics, University of North Carolina at Greensboro, Greensboro, NC 27412, USADepartment of Applied Sciences, Bharati Vidyapeeth’s College of Engineering, New Delhi 110063, IndiaDepartment of Mathematical Sciences, Durham University, Durham DH1 3LE, UKThis study explores the estimation of the mean of a sensitive variable using calibration estimators under measurement error. Three randomized response techniques are evaluated: Partial Randomized Response Technique, Compulsory Randomized Response Technique, and Optional Randomized Response Technique. Theoretical properties of the proposed estimators are analyzed, and a simulation study using real COVID-19 infection data is conducted. Results indicate that the Optional Randomized Response Technique outperforms Partial Randomized Response Technique and Compulsory Randomized Response Technique in terms of efficiency, underscoring its effectiveness and practical utility for improving data quality in sensitive survey settings.https://www.mdpi.com/2227-7390/13/15/2532auxiliary informationcalibration estimatorsmeasurement errorrandomized response technique models |
| spellingShingle | Sat Gupta Pidugu Trisandhya Frank Coolen Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error Mathematics auxiliary information calibration estimators measurement error randomized response technique models |
| title | Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error |
| title_full | Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error |
| title_fullStr | Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error |
| title_full_unstemmed | Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error |
| title_short | Some Calibration Estimators of the Mean of a Sensitive Variable Under Measurement Error |
| title_sort | some calibration estimators of the mean of a sensitive variable under measurement error |
| topic | auxiliary information calibration estimators measurement error randomized response technique models |
| url | https://www.mdpi.com/2227-7390/13/15/2532 |
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