Occasion In Successive Sampling Research Articles

Tuning design weights to deal with non-response in successive sampling

The estimation of finite population mean at current occasion in two occasion successive sampling in presence of non-response is investigated using tuned jackknife estimators. Based on the availability of auxiliary information at population level (Info U) and sample level (Info s) and using tuned jackknife technique, estimators have been proposed. Estimator of variance of proposed estimators have also been discussed. Different cases of occurance of non-response have been explored. The estimators are mutually compared. The properties of these estimators are studied via simulation study using natural population.

Investigation of Competent Estimation Procedure for Estimating the Finite Population Mean at Current Occasion Addressing Non-response in Two-Occasion Successive Sampling

This paper is an effort to investigate the effect of non-response at the current (second) occasion in successive sampling. Using the subsampling non-respondent procedure, some exponential-type estimators have been proposed to estimate the current population mean. Properties of the proposed class of estimators are examined, and respective optimum replacement strategies are derived. Empirical studies are carried out to evaluate the performances of the suggested estimators. The outcomes are interpreted, and appropriate recommendations have been made.

Ratio-Type Exponential Estimator for the Population Mean at the Current Occasion in the Presence of Non-Response in Successive Sampling

In many human surveys, information is in most cases not obtained from all the units in the survey even after some call backs. To cope with this problem, survey statisticians usually consider and adopt the non-respondents sub sampling schemes introduced by Hansen and Hurwitz (1946, Jour. Amer. Statist. Assoc., 41, 517–529). The topic which is of practical importance is the estimation of population mean at the current occasion in two- occasion successive sampling in presence of non-response. In this paper, an alternative to Satici and Kadilar (2011, Hacettepe Jour. Math. Statist. 40(1), 115–124) estimator for the population mean at the current occasion in successive sampling having two occasions is suggested under the missing data case. The minimum mean squared error and optimum fraction of a fresh sample of suggested estimator are obtained. The suggested estimator is compared with the estimator due to Singh and Priyanka (2007, Statistics in Transition. 8(2), 273–292) and Satici and Kadilar (2011, Hacettepe Jour. Math. Statist. 40(1), 115–124) and the efficient conditions for the suggested estimator are obtained. It has been shown theoretically that the proposed class of estimators is more efficient than the Singh and Priyanka (2007) and Satici and Kadilar (2011) estimators. The performance of the suggested class of estimators is examined over Singh and Priyanka (2007) and Satici and Kadilar (2011) estimators with the aid of an empirical study.

Advances in Estimation of Sensitive Issues on Successive Occasions

Surveys related to sensitive issues are accompanied with social desirability response bias which flaw the validity of analysis. This problem became serious when sensitive issues are estimated on successive occasions. The scrambled response technique is an alternative solution as it preserve respondents anonymity. Therefore, the present article endeavours to propose an improved class of estimators for estimating sensitive population mean at current occasion using an innocuous variable in two occasion successive sampling. Detailed properties of the estimators are analysed. Optimum allocation to fresh and matched samples are obtained. Many existing estimators in successive sampling have been modified to work for sensitive population mean estimation under scrambled response technique. The proposed estimators has been compared with recent modified estimators. Theoretical considerations are integrated with empirical and simulation studies to ascertain the efficiency gain derived from the proposed improved class of estimators.

An Improved Mathematical Model Applying Practicable Algorithms

In this article, we have considered the problem of estimation of population variance on two occasion successive sampling. A class of estimators of population variance has been proposed and its asymptotic properties have been discussed. The proposed class of estimators is compared with the sample variance estimator when there is no matching from the previous occasion. Numerical illustrations are also given in support of the present study.

Calibration estimators for quantitative sensitive mean estimation under successive sampling

The problem of estimation of sensitive population mean has been investigated using the item sum technique (IST) with calibration estimators in two occasion successive sampling. Generic sampling design have been assumed at each occasion to define calibration estimators. Properties of the proposed estimators has been discussed including asymptotic variance. Different possible allocation designs for allocating long list and short list samples pertaining to IST has been elaborated. Simulation study using a natural population has also been added to substantiate the theoretical results.

Use of power transformation for estimating the population mean in presence of non-response in successive sampling

Abstract This paper addresses the problem of estimating the population mean at the current occasion in two occasion successive sampling when non-response occurs on the current (second) occasions. Using the power transformation we have suggested classes of estimators of current population mean and their properties are studied. Optimum replacement strategies for the proposed estimators have been given and empirical studies are carried out to assess the performance of estimators. We have made suitable recommendation to the practitioners on the basis of the empirical study.

A Modified Procedure for Estimating the Population Mean in Two-Occasion Successive Sampling

This paper addresses the problem of estimating the current population mean in two occasion successive sampling. Utilizing the readily available information on two auxiliary variables on both occasions and the information on study variable from the previous occasion, some new estimation procedures have been developed. Properties of the proposed estimators have been studied and their respective optimum replacement policies are discussed. Relative comparison of efficiencies of the suggested estimators with the sample mean estimator when there is no matching from previous occasion and the optimum successive sampling estimator when no auxiliary information is used have been incorporated. Empirical study is carried out to judge the merits of the suggested estimators and suitable recommendations are given. We have also added a practical application in order to examine the performance of the proposed estimators. Keywords: Successive sampling, Study variable, Auxiliary variable, Mean squared error, Optimum Replacement Policy

Almost Unbiased Estimation Procedures of Population Mean in Two- Occasion Successive Sampling

The objective of this paper is to construct some unbiased estimators of the current population mean in two-occasion successive sampling. Utilizing the readily available information on an auxiliary variable on both occasions, almost unbiased ratio and regression cum exponential type estimators of current population mean have been proposed. The oretical properties of the proposed estimation procedures have been examined and their respective optimum replacement strategies are for mulated. Performances of the proposed estimators are empirically com pared with (i) the sample mean estimator, when no sample units were matched from the previous occasion and (ii) natural successive sampling estimator when no auxiliary information was used on any occasion. Em pirical results are critically interpreted and suitable recommendations are made to the survey practitioners for their practical applications.

Some effective combinations of available information under non response in two-occasion successive sampling

ABSTRACTThe present work suggests some effective linear combinations of exponential estimators to estimate the current population mean in two occasion successive sampling in presence of non response. Using the subsampling technique of non respondents, estimation procedures have been developed by utilizing information on an auxiliary variable, which is readily available on both occasions. Properties of the proposed estimation procedures have been examined and related optimum replacement strategies are suggested. Empirical studies are carried out to justify the preposition of estimators. Suitable recommendations have been made.

An efficient effective rotation pattern in successive sampling over two occasions

ABSTRACTThis paper addresses the problem of estimating the population mean on the current occasion in two occasion successive sampling. Based on all the readily available information from first and second occasions, a class of estimators is proposed with its properties. It is identified that the estimator recently suggested by Singh and Homa (Journal of Statistical Theory and Practice, 7: 1, 146–155, 2013) is a member of the suggested class of estimators. The correct expression of the mean squared error/variance of the Singh and Homa (2013) estimator is given. The superiority of the suggested class of estimators is discussed with the sample mean estimator when there is no matching, the best combined estimator given in Cochran (1977, p.346) and Singh and Homa (2013) estimator. Optimum replacement policy has been discussed. Numerical illustration is given in support of the present study.

On the use of multi-auxiliary variables to neutralize the effect of non response in two-occasion successive sampling

ABSTRACTIn this work, we have suggested some linear combinations of generalized ratio type estimators in estimation of current population mean when non response occur in two occasion successive sampling. Information on multi-auxiliary variables has been used and sub-sampling of non respondents technique is utilized to cope with the negative effect of non response. Properties of the suggested estimation procedures have been examined and suitable optimum replacement strategies are discussed. Empirical studies are carried out to justify the proposition of estimators. Suitable recommendations have been made.

A General Procedure for Estimating Population Variance in Successive Sampling using Fuzzy Tools

This paper de fines a general class of estimators for estimating population variance on current occasion in two occasion successive sampling. Detail behaviors of the proposed class of estimators have been studied and its optimum replacement strategy has also been discussed. The proposed class of estimators has been compared with the sample variance estimator and the results obtained are demonstrated through empirical studies. Categorization of the dominance ranges of the proposed estimation strategies are deployed through defuzzi cation tools which are followed by suitable recommendations.

Improved Estimation of Current Population Mean Over Two Occasions

This paper addresses 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 .Utilizing the readily available information on two auxiliary variables on both the occasions and information on the study variable from the previous occasion, an efficient estimation procedure of population mean on current (second) occasion has been envisaged. It is to be mentioned that out of the two auxiliary variables one auxiliary variable is positively correlated with the study variable while other is negatively correlated. Behavior of the proposed estimator has 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 portions of the sample at the current (second) occasion. Optimal replacement policy is also discussed. In addition, we support the theoretical results with the aid of numerical examples. Sri Lankan Journal of Applied Statistics 2015;16(1):1-19

Estimation of Population Mean In Successive Sampling by Sub-Sampling Non-Respondents

The estimation of the population mean in mail surveys is investigated in the context of sampling on two occasions where the population mean of the auxiliary variable is available in the presence of non-response only for the current occasion in two occasion successive sampling. The behavior of the proposed estimator is compared with the estimator for the same situation but in the absence of non-response. An empirical illustration demonstrates the performance of the proposed estimator.

Estimation of population mean at current occasion in successive sampling under a super-population model

The present work is an attempt to utilize auxiliary information through a super-population linear model as well as in the structure of estimators for estimating the population mean on current occasion in two-occasion successive sampling. Two different estimators are proposed and their theoretical properties are discussed. Results are supported with empirical studies. Suitable recommendations are made.

A Note on Successive Sampling Over Two Occasions

AbstractIn this note, an attempt has been made to study the effect on MVLUE of a population mean on the second occasion in successive sampling when sample values of correlation and regression coefficients are used in it. It was found that increase in the MSE of derived biased estimator is of the order q2ρ2 which may be negligible till the proportion of unmatched units (q) and correlation coefficient (ρ) are quite small.