A randomized response procedure for multiple-sensitive questions

2011 ◽  
Vol 53 (3) ◽  
pp. 703-718 ◽  
Author(s):  
Lucio Barabesi ◽  
Sara Franceschi ◽  
Marzia Marcheselli
2019 ◽  
Vol 29 (3) ◽  
pp. 894-910 ◽  
Author(s):  
Amanda MY Chu ◽  
Mike KP So ◽  
Thomas WC Chan ◽  
Agnes Tiwari

Sensitive questions are often involved in healthcare or medical survey research. Much empirical evidence has shown that the randomized response technique is useful for the collection of truthful responses. However, few studies have discussed methods to estimate the dependence of sensitive responses of multiple types. This study aims to fill that gap by considering a method based on moment estimation and without using the joint distribution of the responses. In addition to the construction of a covariance matrix for the multiple sensitive questions despite incomplete information due to the randomized response technique design, we can calculate the conditional mean of continuous sensitive responses given as categorical responses and partial correlations among continuous sensitive responses. We conduct a simulation experiment to study the bias and variance of the moment estimator with various sample sizes. We apply the proposed method in a healthcare study of the dependence structure among the responses of a survey concerning health and pressure on college students.


2021 ◽  
Author(s):  
Mursala Khan

Abstract The results of Sample surveys play a vital role in decision making. One of the main issues being faced by survey statisticians during the collection of survey data is the problem of non-response which may affect survey cost and accuracy of estimates. The problem of non-response becomes more severe if the survey contains sensitive questions like related to family planning methods, use of drugs. To diminish the non-response rate arising in the case of direct questioning (DQ) technique, Warner (1965) proposed an indirect survey technique known as the randomized response (RR) technique. He addressed this problem for a cross-sectional data. This method is a well-known procedure that produces more valid responses on sensitive questions in surveys. The method avoids the direct link between respondent’s response and the sensitive question through the help of a randomization device. Thereby protecting respondent’s privacy which in turn greatly increases survey response rate. However, due to the complex nature of panel estimator, the work is missing the in the context of RR technique. To cover this gap, we propose a linear regression model in the context of panel surveys/longitudinal studies under the application of the RR technique. We solve all these issues through simulation study.


Author(s):  
Andy Chong ◽  
Amanda Chu ◽  
Mike So ◽  
Ray Chung

A survey study is a research method commonly used to quantify population characteristics in biostatistics and public health research, two fields that often involve sensitive questions. However, if answering sensitive questions could cause social undesirability, respondents may not provide honest responses to questions that are asked directly. To mitigate the response distortion arising from dishonest answers to sensitive questions, the randomized response technique (RRT) is a useful and effective statistical method. However, research has seldom addressed how to apply the RRT in public health research using an online survey with multiple sensitive questions. Thus, we help fill this research gap by employing an innovative unrelated question design method. To illustrate how the RRT can be implemented in a multivariate analysis setting, we conducted a survey study to examine the factors affecting the intention of illegal waste disposal. This study demonstrates an application of the RRT to investigate the factors affecting people’s intention of illegal waste disposal. The potential factors of the intention were adopted from the theory of planned behavior and the general deterrence theory, and a self-administered online questionnaire was employed to collect data. Using the RRT, a covariance matrix was extracted for examining the hypothesized model via structural equation modeling. The survey results show that people’s attitude toward the behavior and their perceived behavioral control significantly positively affect their intention. This paper is useful for showing researchers and policymakers how to conduct surveys in environmental or public health related research that involves multiple sensitive questions.


1976 ◽  
Vol 44 (2) ◽  
pp. 181 ◽  
Author(s):  
D. G. Horvitz ◽  
B. G. Greenberg ◽  
J. R. Abernathy

Methodology ◽  
2009 ◽  
Vol 5 (4) ◽  
pp. 145-152 ◽  
Author(s):  
L. E. Frank ◽  
A. van den Hout ◽  
P. G. M. van der Heijden

Randomized response (RR) is an interview technique that can be used to protect the privacy of respondents if sensitive questions are posed. This paper explains how to measure change in time if a binary RR question is posed at several time points. In cross-sectional research settings, new insights often gradually emerge. In our setting, a switch to another RR procedure necessitates the development of a trend model that estimates the effect of the covariate time if the dependent variable is measured by different RR designs. We also demonstrate that it is possible to deal with self-protective responses, thus accommodating our trend model with the latest developments in RR data analysis.


2013 ◽  
Vol 43 (2) ◽  
pp. 408-425 ◽  
Author(s):  
Man-Lai Tang ◽  
Qin Wu ◽  
Guo-Liang Tian ◽  
Jian-Hua Guo

1980 ◽  
Vol 73 (8) ◽  
pp. 618-627
Author(s):  
William L. Curlette

Some surprising activities and some of the mathematics behind a comparatively new survey method, the randomized response technique.


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