A new non-randomized multi-category response model for surveys with a single sensitive question: Design and analysis

Man Lai Tang, Guo Liang Tian, Nian Sheng Tang, Zhenqiu Liu

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

In this article, we develop a non-randomized multi-category response model for a single sensitive survey question with multiple outcomes. Unlike existing randomized response models, our proposed model does not require any randomizing device and the respondents are merely asked to answer a non-sensitive question. It thus reduces cost, ensures reproducibility of respondents' answer (i.e., the same respondent gives the same answer if the survey is re-conducted under the non-randomized multi-category model), enhances respondents' trust on the privacy policy, and motivates respondents' cooperation. We show maximum likelihood estimates (MLEs) of cell probabilities can be obtained in closed-form. Bootstrap standard errors and confidence intervals (CIs) of the cell probabilities or their functions are then given. Bayesian estimation via the data augmentation algorithm is developed when prior information on the parameters of interest is available. Simulation studies are conducted to evaluate the performance of the MLEs and CI estimates. A real data set from a questionnaire on sexual activities in Korean adolescents is used to illustrate the proposed design and analysis methods.

Original languageEnglish (US)
Pages (from-to)339-349
Number of pages11
JournalJournal of the Korean Statistical Society
Volume38
Issue number4
DOIs
StatePublished - Dec 1 2009

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Maximum Likelihood Estimate
Confidence interval
Multiple Outcomes
Randomized Response
Data Augmentation
Model Category
Bayesian Estimation
Cell
Reproducibility
Prior Information
Standard error
Questionnaire
Bootstrap
Privacy
Closed-form
Simulation Study
Model
Evaluate
Costs
Estimate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Cite this

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A new non-randomized multi-category response model for surveys with a single sensitive question : Design and analysis. / Tang, Man Lai; Tian, Guo Liang; Tang, Nian Sheng; Liu, Zhenqiu.

In: Journal of the Korean Statistical Society, Vol. 38, No. 4, 01.12.2009, p. 339-349.

Research output: Contribution to journalArticle

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