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Articles by Sat Gupta
On the estimation of population mode in time-scaled surveys using ranked auxiliary information
Advanced search Communications in Statistics - Simulation and Computation Latest Articles Submit an article Journal homepage Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article /doi/full/10.1080/03610918.2026.2719880?needAccess=true Abstract The existing mode estimators are traditionally based on one-time sample surveys, which may adversely affect the estimates due to measurement errors arising during the interviewing process.
Auxiliary information may reduce randomized response technique model privacy
Advanced search Communications in Statistics - Simulation and Computation Latest Articles Submit an article Journal homepage Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article /doi/full/10.1080/03610918.2025.2584091?needAccess=true Abstract It is well known that high quality auxiliary information can improve survey estimates through the implementation of ratio or regression estimators.
Impact of Auxiliary Information and Measurement Errors on Mean Estimation with Mixture Optional Enhanced Trust (MOET) Randomized Response Model
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
A New Difference-Cum-Exponential Type Estimator of Finite Population Mean in Simple Random Sampling
Ayuda Buscar en la ayuda Buscar en la ayuda A New Difference-Cum-Exponential Type Estimator of Finite Population Mean in Simple Random Sampling JAVID SHABBIR [1] ; ABDUL HAQ [1] ; SAT GUPTA [2] [1] Quaid-I-Azam University Department of Statistics [2] The University of North Carolina at Greensboro Department of Mathematics and Statistics Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 37, Nº. 1, 2014, págs.
A Ratio Estimator for the Mean Using a Mixture Optional Enhance Trust (MOET) Randomized Response Model
1. Introduction Researchers in disciplines as far-flung as business, public health, and psychology need answers to questions that are hard to obtain, because they involve sensitive personal information. In such scenarios, “social desirability bias” comes into play. Latkin et al. (2017) describe SDB as the tendency of respondents to underreport socially undesirable attitudes or behaviors and to overreport more desirable attributes [1].
Calibration Estimators with Different Types of Distance Measures Under Stratified Sampling in the Presence of Measurement Error
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Accounting for Measurement Error and Untruthfulness in Binary RRT Models
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
A Mixture Quantitative Randomized Response Model That Improves Trust in RRT Methodology
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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