Modified binary randomized response technique models

Social Desirability Bias (SDB) is the tendency in respondents to answer questions untruthfully in the hope of giving good impression to others. SDB occurs when the survey question is highly sensitive or personal, and responses cause sample statistics to systematically overestimate or underestimate corresponding population parameters. The Randomized Response Technique (RRT) is one of several methods to get around SDB in surveys involving sensitive questions in a face-to-face interview. We first review some of the well-established binary response RRT models including the two-parameter models such as the two-stage RRT model and the optional RRT model. Then, we examine an optional RRT model based on the unrelated question RRT as presented by Gupta, Tuck, Spears Gill, and Crowe (2013). Also, we show another optional RRT model based on the two-stage RRT. Next, we carry out efficiency comparisons between these models and show simulation results. While these two models are all based on the split-sample approach to estimate two unknown parameters of interest ( $\pi$ and $\omega$—the prevalence of sensitive characteristic and the sensitivity level of the underlying question respectively), the next two models utilize the two-question approach instead. One of them relies on the unrelated question RRT model. And the other relies on the two-stage optional RRT model. Again, efficiencies of estimators are compared and simulation results are provided. In the end, simulation results and figures are presented and some conclusions are made regarding which estimator performs better. It turns out that the two-stage optional indirect RRT model with two-question approach performs better than other binary optional RRT models

Randomized Response Technique in Data Mining

Data mining is a process in which data is collected from different sources and resume it in useful information. Data mining is also known as knowledge discovery in database (KDD).Privacy and accuracy are the important issues in data mining when data is shared. A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Most of the methods use random permutation techniques to mask the data, for preserving the privacy of sensitive data. Randomize response techniques were developed for the purpose of protecting surveys privacy and avoiding answers bias mainly. In RR technique it adds certain degree of randomness to the answer to prevent the data. The objective of this thesis is to enhance the privacy level in RR technique using four group schemes. First according to the algorithm random attributes a, b, c, d were considered, Then the randomization have been performed on every dataset according to the values of theta. Then ID3 and CART algorithm was applied on the randomized data. The result shows that by increasing the group, the privacy level will increase

Randomized Response Technique in Data Mining

Data mining is a process in which data is collected from different sources and resume it in useful information. Data mining is also known as knowledge discovery in database (KDD). Privacy and accuracy are the important issues in data mining when data is shared. A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Most of the methods use random permutation techniques to mask the data, for preserving the privacy of sensitive data. Randomize response techniques were developed for the purpose of protecting surveys privacy and avoiding answers bias mainly. In RR technique it adds certain degree of randomness to the answer to prevent the data. The objective of this thesis is t o enhance the privacy level in RR technique using four group schemes. First according to the algorithm random attributes a, b, c, d wer e considered, Then the randomization have been performed on every dataset according to the values of theta. Then ID3 and CART algorithm was applied on the randomized data. The result shows that by increasing the group, the privacy level will increase

Randomized Response Technique in Data Mining

Data mining is a process in which data is collected from different sources and resume it in useful information. Data mining is also known as knowledge discovery in database (KDD).Privacy and accuracy are the important issues in data mining when data is shared. A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Most of the methods use random permutation techniques to mask the data, for preserving the privacy of sensitive data. Randomize response techniques were developed for the purpose of protecting surveys privacy and avoiding answers bias mainly. In RR technique it adds certain degree of randomness to the answer to prevent the data. The objective of this thesis is to enhance the privacy level in RR technique using four group schemes. First according to the algorithm random attributes a, b, c, d were considered, Then the randomization have been performed on every dataset according to the values of theta. Then ID3 and CART algorithm was applied on the randomized data. The result shows that by increasing the group, the privacy level will increase

New Bayesian Estimators for Randomized Response Technique

This paper proposed new Bayesian estimators of the population proportion of a sensitive attribute when life data were collected through the administration of questionnaires on abortion on 300 matured women in some selected hospitals in the metropolis. Assuming both the Kumaraswamy (KUMA) and the generalised (GLS) beta distributions as alternative beta priors, efficiency of the proposed Bayesian estimators was established for a wide interval of the values of the population proportion (. We observed that for small, medium as well as large sample sizes, the developed Bayesian estimators were better in capturing responses from respondents than the conventional simple beta estimator proposed by Hussain and Shabbir (2009a) as  approaches one.

A Survey on Tax Evasion Using Randomized Response Technique

Taxation is a tool used by government to raise revenue. It is also used as an instrument of economic and social policy. This paper adopted Randomized Response Technique to estimate proportions of non-compliance of taxpayers in Akure metropolis as well as analysing socio-demographic variables which may affect those proportions. Survey questionnaires were administered on taxpayers in Akure with a view to collecting data from them. The data collected were analysed using z-test. The findings of this study revealed that among the respondents completing the Randomized Response survey instrument, 47.7% admitted tax evasion by trading goods and not reporting it in tax form, 48.7% admitted evasion by excluding some outside income, 49.8% admitted tax evasion by being paid in cash and not reporting it, 43.7% admitted evasion by hiding investment to avoid payment of tax while 43% admitted evasion by cheating on tax whenever the chances arises respectively

Kim And Warde’s Mixed Randomized Response Technique For Complex Surveys

The randomized response (RR) technique introduced by Warner (1965) was found to be an effective method for reducing answer bias and ensuring better respondent cooperation in estimating the proportion of people in a community bearing a sensitive attribute. Chaudhuri (2001a, 2001b, 2002, 2003) extended Warner’s method and several other well-known RR devices to complex surveys adopting a varying probability sampling design. Kim and Warde (2004) proposed an RR model assuming that the sample is selected with simple random sampling (SRS) with replacement (SRSWR). Here, the method of estimation is presented when sample is chosen with varying selection probabilities and Kim and Warde’s RR procedure is applied for estimating a sensitive proportion. Also illustrated is a numerical example that unequal probability sampling performs better than SRS

Sample Survey on Sensitive Topics: Investigating Respondents' Understanding and Trust in Alternative Versions of the Randomized Response Technique

In social science research, survey respondents hesitate to answer sensitive questions. This explains why traditional self-report surveys often suffer from high levels of non-response and dishonest answers. To overcome these problems, an adjusted questioning technique is necessary. This article examines one such adjusted questioning technique: the randomized response technique. However, in order to obtain reliable and valid data, respondents need to understand and trust this technique. Respondents' understanding and trust are assessed in two online variants of the randomized response technique: (a) forced response and (b) unrelated question. Results show that understanding was significantly higher in the forced-response condition. Respondents' trust, however, was low in both conditions

Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)

Gaining valid answers to so-called sensitive questions is an age-old problem in survey research. Various techniques have been developed to guarantee anonymity and minimize the respondent's feelings of jeopardy. Two such techniques are the randomized response technique (RRT) and the unmatched count technique (UCT). In this study we evaluate the effectiveness of different implementations of the RRT (using a forced-response design) in a computer-assisted setting and also compare the use of the RRT to that of the UCT. The techniques are evaluated according to various quality criteria, such as the prevalence estimates they provide, the ease of their use, and respondent trust in the techniques. Our results indicate that the RRTs are problematic with respect to several domains, such as the limited trust they inspire and non-response, and that the RRT estimates are unreliable due to a strong false "no" bias, especially for the more sensitive questions. The UCT, however, performed well compared to the RRTs on all the evaluated measures. The UCT estimates also had more face validity than the RRT estimates. We conclude that the UCT is a promising alternative to RRT in self-administered surveys and that future research should be directed towards evaluating and improving the technique.sensitive questions, online survey, randomized response technique, unmatched count technique, item count technique, methodological experiment

Logistic regression analysis of employment behavior data using randomized response technique

Direct survey techniques deal with collecting information on sensitive issues data, such as induced abortion, drug addiction, and so on. RR (randomized response) techniques are available for many interviewees, who do not feel comfortable to disclose their personal data due to privacy risks. RR techniques are used in the estimation of the number of people having a sensitive attribute say A. When the research is conducted on the disgraceful or ignominious characteristics of persons like rash driving, tax elusion, induced abortion, testing HIV (human immunodeficiency virus) positive etc., RR techniques are used to make sure that the estimates obtained are efficient and unbiased. During these types of surveys, privacy of the respondent is also managed. Among others, the conflict between efficiency and protection of privacy was also discussed by Nayak in 1994. In RR-related techniques, the SRS (simple random sampling) is statistically used in the sample selection. In this paper, RR procedure is used that allows us to estimate the population proportion in addition to the probability of providing a truthful answer. This study also quantifies a method for the estimation of the model having one variable (univariate) while studying logistic regression, where the dependent variables are subject to RR. In addition, an efficiency comparison is carried out to investigate the performance of the proposed technique. It is also assumed that during the study, the respondents will respond keeping in view the instructions of the RR design. The general idea about findings of current study, though, is so as to perform RR techniques comparatively fine