Randomized Response Techniques Using Maximum Likelihood Estimator

The randomized response (RR) technique with two decks of cards proposed by Odumade and Singh (2009) can always be made more efficient than the RR techniques proposed by Warner (1965), Mangat and Singh (1990), and Mangat (1994) by adjusting the proportion of cards in the decks. Arnab et al. (2012) generalized Odumade and Singh strategy (2009) for complex survey designs and wider class of estimators. In this paper improvement of Arnab et al. (2012) estimator has been made by using maximum likelihood method.     

A GENERALIZED TWO-STAGE RANDOMIZED RESPONSE PROCEDURE IN COMPLEX SAMPLE SURVEYS

The randomized response (RR) technique pioneered by Warner, S.L. (1965) [Randomised response: a survey technique for eliminating evasive answer bias. J. Amer. Statist. Assoc. 60 , 63–69] is a useful tool in estimating the proportion of persons in a community bearing sensitive or socially disapproved characteristics. Mangat, N.S. & Singh, R. (1990) [An alternative rendomized response procedure. Biometrika 77 , 439–442] proposed a modification of Warner's procedure by using two RR techniques. Presented here is a generalized two‐stage RR procedure and derivation of the condition under which the proposed procedure produces a more precise estimator of the population parameter. A comparative study on the performance of this two‐stage procedure and conventional RR techniques, assuming that the respondents' jeopardy level in this proposed method remains the same as that offered by the traditional RR procedures, is also reported. In addition, a numerical example compares the efficiency of the proposed method with the traditional RR procedures.     

A stratified Warner''s randomized response model

This paper proposes a new stratified randomized response model based on Warner's (J. Amer. Statist. Assoc. 60 (1965) 63) model that has an optimal allocation and large gain in precision. It also presents a drawback of the Hong et al. (Korean J. Appl. Statist. 7 (1994) 141) model under their proportional sampling assumption. It is shown that the proposed model is more efficient than the Hong et al. (Korean J. Appl. Statist. 7 (1994) 141) stratified randomized response model. Additionally, it is shown that the estimator based on the proposed method is more efficient than the Warner (J. Amer. Statist. Assoc. 60 (1965) 63), the Mangat and Singh (Biometrika 77 (1990) 439) and the Mangat (J. Roy. Statist. SQC. Ser. B 56 (1) (1994) 93) estimators under the conditions presented in both the case of completely truthful reporting and that of not completely truthful reporting by the respondents.     

An improved two stage randomized response strategy

Mangat and Singh (1990) have suggested a two stage randomized response technique to estimate the proportion of population possessing a sensitive attribute. The procedure was shown to be more efficient than the procedure due to Warner (1965). Recently, Tracy and Osahan (1993) have suggested a modification to the Mangat and Singh (1990) procedure which results in a more efficient strategy in practice. In this paper we propose a modification to the Tracy and Osahan (1993) procedure. The modified procedure is a generalization of Tracy and Osahan (1993) and is always more efficient than their strategy. An empirical study has also been undertaken to find the extent of relative efficiency.     

Pseudo-Bayes and pseudo-empirical Bayes estimators in randomized response sampling

In this article, new pseudo-Bayes and pseudo-empirical Bayes estimators for estimating the proportion of a potentially sensitive attribute in a survey sampling have been introduced. The proposed estimators are compared with the recent estimator proposed by Odumade and Singh [Efficient use of two decks of cards in randomized response sampling, Comm. Statist. Theory Methods 38 (2009), pp. 439–446] and Warner [Randomized response: A survey technique for eliminating evasive answer bias, J. Amer. Statist. Assoc. 60 (1965), pp. 63–69].     

Randomized response model in a matched pair study

The development of randomized response models for personal interview surveys has attracted much attention since the pioneering work of Warner [1965. Randomized response: a survey technique for eliminating evasive answer bias. J. Amer. Statist. Assoc. 60, 63–69]. Several randomized response models have been developed by researchers for collecting data on both qualitative and the quantitative variables, but none of these models discuss matched pair data. In this paper, we develop a new randomized response model and study its application to an important political question.     

Analyzing continuous randomized response data with an indifference-zone selection procedure

A review of the randomized response model introduced by Warner (1965) is given, then a randomized response model applicable to continuous data that considers a mixture of two normal distributions is considered. The target here is not to estimate any parameter, but rather to select the population with the best parameter value. This article provides a study on how to choose the best population between k distinct populations using an indifference-zone procedure. Also, this article includes tables for the required sample size needed in order to have a probability of correct selection higher than some specified value in the preference zone for the randomized response model considered.     

Untruthful answering in repeated randomized response procedures

A simple and clear procedure is given that allows to some degree the estimation and testing of the probability of an untruthful answer in addition to estimating the population proportion by using Warner's (1965) randomized response technique twice.     

Violation of respondent's privacy in moors* model- its rectification through a random group strategy

The primary objective of the randomized response techniques introduced by Warner (1965) and Greenberg et al. (1969) was to protect the privacy of the respondents while eliciting information on sensitive issues. However, Moors' (1971) model, which is considered to be the best in the sense of optimality and convenience to use, fails to protect the privacy of respondents in certain cases. The present paper aims at pointing out this serious draw back. An alternative model termed as 'random group method ' is proposed. The proposed model is free from the above mentioned drawback and provides more efficient estimator as compared to the usual Greenberg at al. 's (1969) model.     

Estimating sensitive proportions by Warner’s randomized response technique using multiple randomized responses from distinct persons sampled

In 1965 Warner pioneered randomized response techniques to estimate the proportion of people bearing a sensitive characteristic. He restricted applying his randomized response device to gather data on sensitive issues from respondents chosen by simple random sampling with replacement (SRSWR). It has spawned numerous ramifications. We present results for the situation where the distinct persons chosen in an SRSWR are identified but each one independently gives a randomized response by Warner’s device, repeated as many times as he/she is selected. Two new estimators are proposed for the sensitive proportion and compared against relevant competitors.     

Generalizations of a contamination model for continuous type random variables

In 1965, Stanley Warner (Warner, 1965) introduced a model for contaminating discrete type random variables. He presented this scheme as being potentially useful in survevs where sensitive in-formation is being gathered. Since that time much research has been conducted and many papers written on the development of these discrete type randomized response models. More recently, atten-tion has been focused on the application of randomized response type models for preservation of confidentiality in existing data files (Boruch 1971 and 1972, Ranney 1975, Felligi 1974, and Inge-marsson 1975). In 1974, Poole (Poole, 1974) introduced a randomized response model for a positive continuous type random variable which was basically a continuous variable analog of the discrete variable Warner model. In this paper the results of the 1974 paper are extended to a lt-dimensional continuous type random variable in k-dimensional Euclidean space.     

Using Randomized Response to Estimate the Proportion and Truthful Reporting Probability in a Dichotomous Finite Population

In this paper, an alternative randomized response procedure is given that allows us to estimate the population proportion in addition to the probability of providing a truthful answer. It overcomes a difficulty associated with traditional randomized response techniques. Properties of the proposed estimators as well as sample size allocations are studied. In addition, an efficiency comparison is carried out to investigate the performance of the proposed technique.     

A Two-Stage Sequential Sampling Scheme for Warner's Randomized Response Model

Abstract

In this article we revisit Warner's (Warner, S. L. (1965 Warner, S. L. 1965. Randomized Response: a survey technique for elimination evasive answer bias. Journal of the American Statistical Association, 60: 63–69. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Randomized response: a survey technique for elimination evasive answer bias. Journal of the American Statistical Association 60:63–69) randomize response model for estimating the proportion of “sensitive” attributed in a population and propose a two-stage sequential sampling procedure for it. We show that the new procedure can potentially reduce, on the average, the number of interviewees surveyed in the study while allowing instances with smaller error of estimation. The properties and some of the attractive features of the randomized response two-stage sequential sampling estimation procedure is discussed as illustrated.     

Admissibility of a variance estimator in finite population sampling under Warner's randomized response plan with multiple responses

ABSTRACT

Let P be the proportion of individuals in a finite population possessing a sensitive attribute. We consider the problem of unbiased estimation of (i) the variance of a linear unbiased estimator of P and (ii) the population variance P (1—P) for a given probability sampling design under Warner's (1965 Warner, S.L. (1965). Randomized response - A survey technique for eliminating evasive answer bias. J. Amer. Statist. Assoc. 60:63–69.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) randomized response (RR) plan when independent responses are obtained from each sampled individual as many times as he/she is selected in the sample and prove the admissibility of a quadratic unbiased estimator for each.     

Optional versus compulsory randomized response techniques in complex surveys

In estimating the proportion of people bearing a sensitive attribute in a community, to mitigate possible evasive answer biases, Warner (J. Amer. Statist. Assoc. 60 (1965) 63) introduced a technique of randomized response (RR) in human surveys, by way of protecting individual privacy. Chaudhuri and Mukerjee (Calcutta Statist. Assoc. Bull. 34 (1985) 225; Randomized Response: Theory and Techniques, Marcel Dekker, New York) presented a modification allowing a direct response (DR) option to whom the attribute does not appear to be stigmatizing enough. Warner himself and many of his followers restrict the application of their RR devices to surveys with selection exclusively by ‘simple random sampling with replacement’. Chaudhuri (J. Statist. Plann. Inference 34 (2001a) 37; Pakistan J. Statist. 17 (3) (2001b) 259; Calcutta Statist. Assoc. Bull. 52 (205–208) (2002) 315) showed the efficacy of some of these devices when sample selection is by general unequal probabilities possibly even without replacement. Here, we present theories for unbiased estimation of the proportion along with unbiased estimation of the variances of the estimators when ‘compulsory’ or ‘optional’ RR's are gathered from persons sampled with varying probabilities. Gains in efficiency by allowing DR option rather than RR compulsion are illustrated numerically through simulation from data.     

Analyzing Hybrid Randomized Response Data with a Binomial Selection Procedure

The operating characteristics (OCs) of an indifference-zone ranking and selection procedure are derived for randomized response binomial data. The OCs include tables and figures to facilitate tradeoffs between sample size and a stated probability of a correct selection, i.e., correctly identifying the binomial population (out of k ≥ 2) characterized by the largest probability of success. Measures of efficiency are provided to assist the analyst in selection of an appropriate randomized response design for the collection of the data. A hybrid randomized response model, which includes the Warner model and the Greenberg et al. model, is introduced to facilitate comparisons among a wider range of statistical designs than previously available. An example comparing failure rates of contraceptive methods is used to illustrate the use of these new results.     

On the comparison of Warner's and unrelated question randomized response plans for estimating sensitive finite population proportions

We consider the problem of estimation of a finite population proportion (P) related to a sensitive attribute under Warner's (1965 Warner, S.L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc. 60:63–69.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) randomized response plan and the unrelated question plan due to Horvitz et al. (1967 Warner, S.L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc. 60:63–69.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and prove that for a given probability sampling design, given any linear unbiased estimator (LUE) of P based on Warner's (1965 Warner, S.L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc. 60:63–69.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) plan with any given value of the plan parameter, there exists an LUE of P based on the unrelated question plan with a uniformly smaller variance for suitable choices of the plan parameters. Assuming that only the attribute is sensitive but its complement is innocuous, the same is also shown to be true when the plan parameters for the two plans are so chosen so that both offer the same specified level of privacy.     

On the heterogeneity of proportions

The comparison amongmproportions can be viewed as the clustering of the means of Bernoulli trials. By introducing a distribution which is supported on the means of Bernoulli trials, we suggest a moment method approach to determine the center of the clusters. We also suggest using model selection criteria rather than the usual testing hypothesis approach to determine the grouping of the means. The discrepancy function for all possible models are compared based on the bootstrap results.     

A new unrelated question randomized response model

In this paper, we extend the work of Gjestvang and Singh [A new randomized response model, J. R. Statist. Soc. Ser. B (Methodological) 68 (2006), pp. 523–530] to propose a new unrelated question randomized response model that can be used for any sampling scheme. The interesting thing is that the estimator based on one sample is free from the use of known proportion of an unrelated character, unlike Horvitz et al. [The unrelated question randomized response model, Social Statistics Section, Proceedings of the American Statistical Association, 1967, pp. 65–72], Greenberg et al. [The unrelated question randomized response model: Theoretical framework, J. Amer. Statist. Assoc. 64 (1969), pp. 520–539] and Mangat et al. [An improved unrelated question randomized response strategy, Calcutta Statist. Assoc. Bull. 42 (1992), pp. 167–168] models. The relative efficiency of the proposed model with respect to the existing competitors has been studied.     

Generalized geometric distribution of order k: A flexible choice to randomize the response

This article focuses on the improvement of a well-celebrated randomized response technique of Kuk. A generalized randomized response technique is suggested. In particular, the generalized geometric distribution of order k is introduced as a randomization device for estimating the population proportion of a rare sensitive attribute. The proposed randomized response technique includes Singh and Grewal and Hussain et al. techniques as its special cases. Through numerical illustrations, it is established that the suggested technique is superior to the Kuk, Singh and Grewal, and Hussain et al. techniques. Flexibility of the proposed technique is also discussed.