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This article addresses the problem of estimating the proportion πS of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is more efficient than Kim and Warde stratified randomized response model and Mangat model. [ABSTRACT FROM AUTHOR]

This paper intends to put emphasis on the role of two auxiliary variables on both the occasions to improve the precision of estimates at current (second)occasion in two-occasion successive sampling. There are different situations when (i) the information on the single auxiliary variablez1is readily available on both the occasions and positively correlated with the study variabley, (ii) the information on the single auxiliary variablez2is readily available on both the occasions and negatively correlated with the study variabley, (iii) the information on two auxiliary variables (z1,z2) are available on both the occasions, with one auxiliary variablez1is positively correlated and the other negatively correlated with the study variabley; these have been discussed through proposing three estimators (one in each situation) of the population meanon the current (second) occasion and analyzing their properties. The properties of the proposed estimators have been studied and compared with the sample mean estimator when there is no matching from the previous occasion and traditional successive sampling estimator, which is a linear combination of the means of the matched and unmatched portion of the sample at the current (second) occasion. Optimal replacement policy is discussed. Empirical studies are carried out to show the domination of the recommended estimators. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating a general parameter using information on an auxiliary variableX. We have suggested a class of exponential-type ratio estimators for the parameter and its properties are studied. It is identified that the estimators due to Upadhyaya et al. [Journal of Statistical Theory and Practice (2011), 5(2), 285–302] and Yadav and Kadilar [Revista Columbiana de Estadistica, (2013), 36(1), 145–152] are members of the proposed estimator. We have also shown that the suggested estimator is more efficient than the estimators of Upadhyaya et al. (2011) and Yadav and Kadilar (2013). Numerical illustration is provided in support of the present study. [ABSTRACT FROM AUTHOR]

This paper suggests a new stratified randomized response model based on Kuk's [Biometrika (1990), 77, 2, pp.436–438] model that has Neyman allocation and considerable gain in precision. It has been identified that the stratified randomized response models due to Kim and Warde (2004), Kim and Elam's (2005), and Kim and Elam's (2007) are members of the proposed model. It is shown that the proposed model is more efficient than Kuk's (1990) model both theoretically and empirically. The results of this paper are also extended in the situation when trials are repeated. [ABSTRACT FROM AUTHOR]

The crux of this article is to estimate the mean of the number of persons possessing a rare sensitive attribute based on the Mangat (1991) randomization device by utilizing the Poisson distribution in simple random sampling and stratified sampling. Properties of the proposed randomized response (RR) model have been studied along with recommendations. It is also shown that the proposed model is more efficient than that of Land et al. (2011) in simple random sampling and that of Lee et al. (2013) in stratified random sampling when the proportion of persons possessing a rare unrelated attribute is known. Numerical illustrations are also given in support of the present study. [ABSTRACT FROM AUTHOR]

This article suggests the class of estimators of population mean of study variable using various parameters related to an auxiliary variable with its properties in simple random sampling. It has been identified that the some existing estimator/classes of estimators are members of suggested class. It has been found theoretically as well as empirically that the suggested class is better than the existing methods. [ABSTRACT FROM AUTHOR]

Taking clue from the pioneer work of Singh and Sedory (2013), we have suggested a new stratified randomized response (RR) model. The properties of the suggested stratified RR model have been studied under proportional and “Neyman” allocations. The study has been also carried out in the presence of crude prior estimates. Numerical illustrations are also given in support of the present study. [ABSTRACT FROM AUTHOR]

This article considers the problem of estimating the population mean on the current (second) occasion using multi-auxiliary information in successive sampling over two occasions. A general class of estimators is proposed for estimating population mean on the current occasion and expressions for bias and mean square error for these estimators are obtained up to first degree of approximation. The minimum variance bound estimator in the proposed class is discussed. Many popular estimators have been shown to belong to this class. Optimum replacement policy is also discussed. Finally, the superiority of the proposed class of estimators over multivariate version of chain type ratio estimator envisaged by Singh (2005) is established empirically. [ABSTRACT FROM AUTHOR]

This paper aimed at providing an efficient new unbiased estimator for estimating the proportion of a potentially sensitive attribute in survey sampling. The suggested randomization device makes use of the means, variances of scrambling variables, and the two scalars lie between “zero” and “one.” Thus, the same amount of information has been used at the estimation stage. The variance formula of the suggested estimator has been obtained. We have compared the proposed unbiased estimator with that of Kuk (1990) and Franklin (1989), and Singh and Chen (2009) estimators. Relevant conditions are obtained in which the proposed estimator is more efficient than Kuk (1990) and Franklin (1989) and Singh and Chen (2009) estimators. The optimum estimator (OE) in the proposed class of estimators has been identified which finally depends on moments ratios of the scrambling variables. The variance of the optimum estimator has been obtained and compared with that of the Kuk (1990) and Franklin (1989) estimator and Singh and Chen (2009) estimator. It is interesting to mention that the “optimum estimator” of the class of estimators due to Singh and Chen (2009) depends on the parameter π under investigation which limits the use of Singh and Chen (2009) OE in practice while the proposed OE in this paper is free from such a constraint. The proposed OE depends only on the moments ratios of scrambling variables. This is an advantage over the Singh and Chen (2009) estimator. Numerical illustrations are given in the support of the present study when the scrambling variables follow normal distribution. Theoretical and empirical results are very sound and quite illuminating in the favor of the present study. [ABSTRACT FROM PUBLISHER]

The crux of this paper is to estimate the mean of the number of persons possessing a rare sensitive attribute based on the Mangat (1992) randomization device by utilizing the Poisson distribution in survey sampling. It is shown that the proposed model is more efficient than Land et al. (2011) when the proportion of persons possessing a rare unrelated attribute is known. Properties of the proposed randomized response model have been studied along with recommendations. We have also extended the proposed model to stratified random sampling on the lines of Lee et al. (2013). It has been also shown that the proposed estimator is better than Lee et al.'s (2013) estimator. Numerical illustrations are also given in support of the present study. [ABSTRACT FROM PUBLISHER]

This paper applies stratified random sampling using Neyman allocation to Mangat et al. (1992) unrelated question randomized response (RR) strategy for both completely truthful reporting and less than completely truthful reporting. It is shown that, for the prior information given, our new model is more efficient in terms of variance (in the case of completely truthful reporting) and mean square error (in terms of less than completely truthful reporting) than Kim and Elam's (2007) model. Numerical illustrations and graphs are also given in support of the present study. [ABSTRACT FROM PUBLISHER]

This paper proposes an alternative two-stage stratified randomized response model based on Tracy and Osahan (1999) model that has an optimal allocation and large gain in precision. It is also shown that the proposed model is more efficient than Kim and Warde (2004) and Kim and Elam (2005) stratified randomized response models under the conditions presented in both the cases of completely truthful reporting and that of not completely truthful reporting by the respondents. Numerical illustrations and graphs are also given in support of the present study. [ABSTRACT FROM PUBLISHER]

In this article, we propose a generalized ratio-cum-product type exponential estimator for estimating population mean in stratified random sampling. Asymptotic expression of the bias and mean squared error of the proposed estimator are obtained. Asymptotic optimum estimator in the proposed estimator has been obtained with its mean squared error formula. Conditions under which the proposed estimator is more efficient than usual unbiased estimator, combined ratio and product type estimators, Singh et al. (2008) estimators and Tailor and Chouhan (2014) estimator are obtained. An empirical study has also been carried out. [ABSTRACT FROM PUBLISHER]

This paper discusses the problem of estimating the finite population variance using auxiliary information in presence of measurement errors. We have suggested a class of estimators and its properties are studied under large sample approximation. It has been shown that the usual unbiased estimator and the estimators due to Sharma and Singh [A generalized class of estimators for finite population variance in presence of measurement errors, Journal of Modern Applied Statistical Methods, (2013), 12(2), 231-241.] are members of the proposed class of estimators. An alternative expression of the mean squared error of one the estimator due to Sharma and Singh [A generalized class of estimators for finite population variance in presence of measurement errors, Journal of Modern Applied Statistical Methods, (2013), 12(2), 231-241.] is also provided. The relative performance of various estimators has been examined through an empirical study. [ABSTRACT FROM AUTHOR]

In this article we suggest some improved version of estimators of scale parameter of Morgenstern-type bivariate uniform distribution (MTBUD) based on the observations made on the units of the ranked set sampling regarding the study variableYwhich is correlated with the auxiliary variableX, when (X,Y) follows a MTBUD. We also suggest some linear shrinkage estimators of scale parameter of Morgenstern type bivariate uniform distribution (MTBUD). Efficiency comparisons are also made in this work. [ABSTRACT FROM PUBLISHER]

In this paper we have suggested a class of unbiased estimators of πS, the proportion of respondents possessing a sensitive attribute A using mixed randomized response model. The variance of the proposed class of estimators has been obtained. In addition to Kim and Warde's (2005) estimator, several other acceptable estimators of πShave been identified from the proposed class for suitable weights. It has been shown that the newly identified estimators are more efficient than the Kim and Warde's (2005) estimator. Numerical illustrations and graphs are also given in support of the present study. [ABSTRACT FROM AUTHOR]

In this article, first we obtained the correct mean square error expression of Gupta and Shabbir’s linear weighted estimator of the ratio of two population proportions. Later we suggested the general class of ratio estimators of two population proportions. The usual ratio estimator, Wynn-type estimator, Singh, Singh, and Kaur difference-type estimator, and Gupta and Shabbir estimator have been found to be members of the suggested class. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating the population mean of the study variable y using information on an auxiliary variable x. A class of Exponential-Type Estimators has been suggested along with its properties under large sample approximation. It is identified that the usual Unbiased Estimator, Product-Type and Ratio-Type Exponential Estimators are members of the proposed class of Exponential-Type Estimators. It has been shown that the proposed class of Exponential-Type Estimators is more efficient than the usual Unbiased Estimator and some existing Estimators. An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This paper suggested an alternative ratio-cum-product type class of estimators of population mean using exponentiation method in simple random sampling. Approximate bias and mean squared error formulae of the suggested class of estimators have been obtained up to the first order of approximation. Asymptotic optimum estimator in the suggested class of estimators has been obtained with its mean squared error formula. Regions of preferences have been obtained under which the suggested class of estimators has been better than the usual unbiased, ratio and product estimators and the estimators according to Singh and Agnihotri (2008). Some examples are cited with numerical study. [ABSTRACT FROM PUBLISHER]

In this paper, an improved new additive model has been proposed. The proposed model is found to be more efficient than the randomized response models studied by Gjestvang and Singh (2009) and Singh (2010). The relative efficiency of the proposed model has been studied with respect to the Gjestvang and Singh (2009) and Singh (2010) model. It is found that the envisaged model is superior to those additive models earlier considered by Gjestvang and Singh (2009) and Singh (2010).Numerical illustrations are also given in support of the present study. [ABSTRACT FROM AUTHOR]

In this article, we have suggested a new modified mixed randomized response (RR) model and studied its properties. It is shown that the proposed mixed RR model is always more efficient than the Kim and Warde’s mixed RR model. The proposed mixed RR model has also been extended to stratified sampling. Numerical illustrations and graphical representations are also given in support of this study. [ABSTRACT FROM AUTHOR]