A new privacy-protecting survey design for multichotomous sensitive variables

DOI10.1007/s00184-012-0406-8zbMath1304.62032OpenAlexW1983239978MaRDI QIDQ464366

Heiko Groenitz

Publication date: 17 October 2014

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00184-012-0406-8

zbMATH Keywords

EM algorithmcirculant matrixrandomized response modelnonrandomized response methoduntruthful answers

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05)

Related Items (9)

Analyzing efficiency for the multi-category parallel method ⋮ A new variant of the parallel regression model with variable selection in surveys with sensitive attribute ⋮ Risk-optimal estimators for survey procedures with certain indirect questions ⋮ A covariate nonrandomized response model for multicategorical sensitive variables ⋮ Estimation of parameters of logistic regression for two-stage randomized response technique ⋮ Valid estimates for repeated randomized response methods ⋮ Logistic regression analyses for indirect data ⋮ Using prior information in privacy-protecting survey designs for categorical sensitive variables ⋮ Applying the nonrandomized diagonal model to estimate a sensitive distribution in complex sample surveys

Uses Software

• bootstrap

Cites Work

• Two new models for survey sampling with sensitive characteristic: design and analysis
• A new non-randomized multi-category response model for surveys with a single sensitive question: design and analysis
• Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
• Matrix Algebra
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