Poisson-Poisson item count techniques for surveys with sensitive discrete quantitative data

DOI10.1007/s00362-017-0895-7zbMath1432.62025OpenAlexW2601028443MaRDI QIDQ2010824

Qin Wu, Guo-Liang Tian, Yin Liu, Man-Lai Tang

Publication date: 28 November 2019

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-017-0895-7

zbMATH Keywords

randomized response techniqueitem count techniquemultiple-trial designsensitive discrete quantitative datasingle-trial design

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Factorial statistical designs (62K15)

Related Items (1)

A new variant of the parallel regression model with variable selection in surveys with sensitive attribute

Cites Work

• Multivariate Regression Analysis for the Item Count Technique
• Improvements and extensions of the item count technique
• Item count technique in estimating the proportion of people with a sensitive feature
• A variant of the parallel model for sample surveys with sensitive characteristics
• Accounting for self-protective responses in randomized response data from a social security survey using the zero-inflated Poisson model
• Indirect Questioning in Sample Surveys
• Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
• A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• The Efficiency of the Multiple Trial Randomized Response Technique
• A Comparison of Three Randomized Response Models for Quantitative Data

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