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Incomplete Categorical Data Design

Non-randomized Response Techniques for Sensitive Questions in Surveys

By Guo-Liang Tian, Man-Lai Tang

To Be Published July 22nd 2013 by Chapman and Hall/CRC – 314 pages

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Description

Unlike the established randomized response (RR) technique, non-randomized response (NRR) techniques yield reproducible results in survey design and analysis. This book presents new techniques designed to overcome the bias inherent in posing sensitive questions in sociological or behavioral science surveys, without requiring a means of randomization. The authors provide a systematic introduction to NRR techniques that can overcome the limitations of RR techniques, combining the strengths of existing approaches, such as RR models, incomplete data design, expectation-maximization algorithm, data augmentation algorithm, and bootstrap method.

Contents

Introduction. The Crosswise Model. The Triangular Model. Sample Size Determination for the Triangular Model. The Multi-Category Response Model. The Hidden Sensitivity Model for Two Sensitive. A Survey Design for One Sensitive Question and One Non-Sensitive Question. Appendices.

Name: Incomplete Categorical Data Design: Non-randomized Response Techniques for Sensitive Questions in Surveys (Hardback) – Chapman and Hall/CRC 
Description: By Guo-Liang Tian, Man-Lai Tang. Unlike the established randomized response (RR) technique, non-randomized response (NRR) techniques yield reproducible results in survey design and analysis. This book presents new techniques designed to overcome the bias inherent in posing sensitive...
Categories: Quantitative Methods, Statistics for the Biological Sciences, Statistical Theory & Methods