Logistic regression analyses for indirect data

DOI10.1080/03610926.2017.1364387OpenAlexW2749628463MaRDI QIDQ5154043

Heiko Groenitz

Publication date: 1 October 2021

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2017.1364387

zbMATH Keywords

randomized responsemissing datasensitive questionstatistical disclosure controlnon-randomized responseitem count technique

Mathematics Subject Classification ID

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

Cites Work

• Multivariate Regression Analysis for the Item Count Technique
• A new privacy-protecting survey design for multichotomous sensitive variables
• Improvements and extensions of the item count technique
• Two new models for survey sampling with sensitive characteristic: design and analysis
• Multi-category parallel models in the design of surveys with sensitive questions
• The logistic regression model with response variables subject to randomized response
• On the analysis of some multivariate randomized response designs for categorical data
• A covariate nonrandomized response model for multicategorical sensitive variables
• 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
• An alternative randomized response procedure
• Asking sensitive questions indirectly
• The Calculation of Posterior Distributions by Data Augmentation
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Logistic regression analyses for indirect data