Efficient estimation of population variance of a sensitive variable using a new scrambling response model [PDF]
Scientific Reports, 2023 This study introduces a pioneering scrambling response model tailored for handling sensitive variables. Subsequently, a generalized estimator for variance estimation, relying on two auxiliary information sources, is developed following this novel model ...
Iram Saleem +4 more
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A Survey Design for a Sensitive Binary Variable Correlated with Another Nonsensitive Binary Variable [PDF]
Journal of Probability and Statistics, 2013 Tian et al. (2007) introduced a so-called hidden sensitivity model for evaluating the association of two sensitive questions with binary outcomes. However, in practice, we sometimes need to assess the association between one sensitive binary variable (e ...
Jun-Wu Yu, Yang Lu, Guo-Liang Tian
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A generalized class of estimators for sensitive variable in the presence of measurement error and non-response. [PDF]
PLoS ONE, 2022 In this paper, a general class of estimators is proposed for estimating the finite population mean for sensitive variable, in the presence of measurement error and non-response in simple random sampling.
Erum Zahid +4 more
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Calibrated-Two Optional Randomized Response Techniques (C-TORRT) for the estimation of quantitative sensitive variable information. [PDF]
PLoS ONEAccurate estimation of sensitive quantitative variables remains a challenge in survey research due to respondents' reluctance to disclose truthful information. While existing randomized response techniques (RRT) offer privacy protection, many suffer from
Mojeed Abiodun Yunusa +4 more
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An efficient estimator of population variance of a sensitive variable with a new randomized response technique [PDF]
HeliyonIn sampling theory, a majority of the available estimators of population variance are designed for use with non-sensitive variables only. Such estimators cannot perform efficiently when the variable of interest is of sensitive nature, such as use of ...
Muhammad Azeem +4 more
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Inversion model of soil salinity in alfalfa covered farmland based on sensitive variable selection and machine learning algorithms [PDF]
PeerJPurpose Timely and accurate monitoring of soil salinity content (SSC) is essential for precise irrigation management of large-scale farmland. Uncrewed aerial vehicle (UAV) low-altitude remote sensing with high spatial and temporal resolution provides a ...
Hong Ma +5 more
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Scrambling Reports: New Estimators for Estimating the Population Mean of Sensitive Variables
Mathematics, 2023 Warner proposed a methodology called randomized response techniques, which, through the random scrambling of sensitive variables, allows the non-response rate to be reduced and the response bias to be diminished. In this document, we present a randomized
Pablo O. Juárez-Moreno +3 more
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Advances in Estimation of Sensitive Issues on Successive Occasions
Statistica, 2020 Surveys related to sensitive issues are accompanied with social desirability response bias which flaw the validity of analysis. This problem became serious when sensitive issues are estimated on successive occasions.
Kumari Priyanka, Pidugu Trisandhya
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Cost-Sensitive Variable Selection for Multi-Class Imbalanced Datasets Using Bayesian Networks
Mathematics, 2021 Multi-class classification in imbalanced datasets is a challenging problem. In these cases, common validation metrics (such as accuracy or recall) are often not suitable.
Darío Ramos-López, Ana D. Maldonado
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Inferring the Population Mean with Second-Order Information in Online Social Networks
Entropy, 2018 With the increasing use of online social networking platforms, online surveys are widely used in many fields, e.g., public health, business and sociology, to collect samples and to infer the population characteristics through self-reported data of ...
Saran Chen +3 more
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