Incomplete Categorical Data Design: Non-Randomized Response Techniques for Sensitive Questions in Surveys, 1st Edition (e-Book) book cover

Incomplete Categorical Data Design

Non-Randomized Response Techniques for Sensitive Questions in Surveys, 1st Edition

By Guo-Liang Tian

Chapman and Hall/CRC

319 pages

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Hardback: 9781439855331
pub: 2013-08-17
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Description

Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando

Table of Contents

Introduction. The Crosswise Model. The Triangular Model. Sample Size Determination for the Crosswise and Triangular Models. The Multi-Category Triangular Model. The Hidden Sensitivity Model. The Parallel Model. Sample Size Calculation for the Parallel Model. The Multi-Category Parallel Model. A Variant of the Parallel Model. The Combination Questionnaire Model. Appendices. References. Indices.

About the Author

Guo-Liang Tian is an associate professor of statistics in the Department of Statistics and Actuarial Science at the University of Hong Kong. Dr. Tian has published more than 60 (bio)statistical and medical papers in international peer-reviewed journals on missing data analysis, constrained parameter models and variable selection, sample surveys with sensitive questions, and cancer clinical trial and design. He is also the co-author of two books. He received a PhD in statistics from the Institute of Applied Mathematics, Chinese Academy of Science.

Man-Lai Tang is an associate professor in the Department of Mathematics at Hong Kong Baptist University. Dr. Tang is an editorial board member of Advances and Applications in Statistical Sciences and the Journal of Probability and Statistics; associate editor of Communications in Statistics-Theory and Methods and Communications in Statistics-Simulation and Computation; and editorial advisory board member of the Open Medical Informatics Journal. His research interests include exact methods for discrete data, equivalence/non-inferiority trials, and biostatistics. He received a PhD in biostatistics from UCLA.

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General