Randomized response and the binary probit model

DOI10.1016/j.econlet.2004.07.013zbMath1255.62028OpenAlexW2034708769MaRDI QIDQ1927740

Gerd Ronning

Publication date: 2 January 2013

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: http://www.iaw.edu/RePEc/iaw/pdf/iaw_dp_10.pdf

zbMATH Keywords

asymptotic efficiencymaximum likelihoodmisclassificationstatistical disclosurepost randomization

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Sampling theory, sample surveys (62D05)

Related Items (3)

Microeconometric models and anonymized micro data ⋮ Some recent advances in measurement error models and methods ⋮ On Invariant Post‐randomization for Statistical Disclosure Control

Cites Work

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• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Model assisted survey sampling
• Misclassification of the dependent variable in a discrete-response setting
• Estimating linear regressions with mismeasured, possibly endogenous, binary explanatory variables
• Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
• Randomized Response, Statistical Disclosure Control and Misclassificatio: a Review

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