An alternative to unrelated randomized response techniques with logistic regression analysis
| Autor: | Su Hao Tu, Chin-Shang Li, Shu Hui Hsieh, Shen-Ming Lee |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Statistics and Probability
Conditional likelihood Computer science Randomized Response Technique Maximum likelihood 05 social sciences 050401 social sciences methods Logistic regression 01 natural sciences Article 010104 statistics & probability 0504 sociology Respondent Statistics Econometrics Randomized response 0101 mathematics Statistics Probability and Uncertainty |
| Zdroj: | Statistical Methods & Applications. 25:601-621 |
| ISSN: | 1613-981X 1618-2510 |
| DOI: | 10.1007/s10260-016-0351-1 |
| Popis: | The randomized response technique (RRT) is an important tool that is commonly used to protect a respondent’s privacy and avoid biased answers in surveys on sensitive issues. In this work, we consider the joint use of the unrelated-question RRT of Greenberg et al. (J Am Stat Assoc 64:520–539, 1969) and the related-question RRT of Warner (J Am Stat Assoc 60:63–69, 1965) dealing with the issue of an innocuous question from the unrelated-question RRT. Unlike the existing unrelated-question RRT of Greenberg et al. (1969), the approach can provide more information on the innocuous question by using the related-question RRT of Warner (1965) to effectively improve the efficiency of the maximum likelihood estimator of Scheers and Dayton (J Am Stat Assoc 83:969–974, 1988). We can then estimate the prevalence of the sensitive characteristic by using logistic regression. In this new design, we propose the transformation method and provide large-sample properties. From the case of two survey studies, an extramarital relationship study and a cable TV study, we develop the joint conditional likelihood method. As part of this research, we conduct a simulation study of the relative efficiencies of the proposed methods. Furthermore, we use the two survey studies to compare the analysis results under different scenarios. |
| Databáze: | OpenAIRE |
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