Transformed ratio type estimators for the population mean in the presence of nonresponse

Khare, B. B.; Srivastava, Shikha

doi:10.1080/03610929708832012

Cited by 83 publications

(30 citation statements)

References 3 publications

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“…It may be noted from equations (60) and (74) that the dominance of the class of estimators 2 T over 3 t and 4 T over 6 t are difficult to establish theoretically.…”

Section: Efficiency Comparisons Of the Proposed Classes Of Estimatorsmentioning

confidence: 99%

Some Estimation Procedures in Presence of Non-Response in Two-Phase Sampling

Bandyopadhyay¹,

Singh

2015

Sri Lankan J App Stats

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“…It may be noted from equations (60) and (74) that the dominance of the class of estimators 2 T over 3 t and 4 T over 6 t are difficult to establish theoretically.…”

Section: Efficiency Comparisons Of the Proposed Classes Of Estimatorsmentioning

confidence: 99%

Some Estimation Procedures in Presence of Non-Response in Two-Phase Sampling

Bandyopadhyay¹,

Singh

2015

Sri Lankan J App Stats

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“…When the population mean X of the auxiliary information x is known, the work of Rao (1986) has been further extended by Khare and Srivastava (1997), Singh and Kumar (2008), Kumar (2012), Kumar and Vishwanathaiah (2013), Olufadi and Kumar (2014) and Chanu and Singh (2015) in presence of non-response.…”

Section: Introductionmentioning

confidence: 99%

Finite Population Mean Estimation through a Two-Parameter Ratio Estimator Using Auxiliary Information in Presence of Non-Response

Pal

Singh

2016

Journal of Applied Mathematics, Statistics and Informatics

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In surveys covering human populations it is observed that information in most cases are not obtained at the first attempt even after some callbacks. Such problems come under the category of non-response. Surveys suffer with non-response in various ways. It depends on the nature of required information, either surveys is concerned with general or sensitive issues of a society. Hansen and Hurwitz (1946) have considered the problem of non-response while estimating the population mean by taking a subsample from the non-respondent group with the help of extra efforts and an estimator was suggested by combining the information available from the response and nonresponse groups. We also mention that in survey sampling auxiliary information is commonly used to improve the performance of an estimator of a quantity of interest. For estimating the population mean using auxiliary information in presence of nonresponse has been discussed by various authors. In this paper, we have developed estimators for estimating the population mean of the variable under interest when there is non-response error in the study as well as in the auxiliary variable. We have studied properties of the suggested estimators under large sample approximation. Comparison of the suggested estimators with usual unbiased estimator reported by Hansen and Hurwitz (1946) and the ratio estimator due to Rao (1986) have been made. The results obtained are illustrated with aid of an empirical study.

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“…Motivated by Khare and Kumar's [6] work, Khare and Rehman [7] used a coefficient of variation of study variable y along with the population mean of auxiliary variable to improve the efficiency of ratio in regression type estimators in the presence of non-response by proposing the following estimator:…”

Section: Introductionmentioning

confidence: 99%

“…where [6] proposed estimators utilizing the coefficient of variation of study variable y in the estimation of population mean using the benefits of auxiliary variable in the presence of non-response. Motivated by Khare and Kumar's [6] work, Khare and Rehman [7] used a coefficient of variation of study variable y along with the population mean of auxiliary variable to improve the efficiency of ratio in regression type estimators in the presence of non-response by proposing the following estimator:…”

Section: Introductionmentioning

confidence: 99%

An Efficient General Family of Estimators for Population Mean in the Presence of Non-Response

Rachokarn

Lawson

2017

J. Math. Fund. Sci.

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Abstract. This paper presents a new general family of estimators to estimate the population mean of study variable y in the presence of non-response when utilizing a known coefficient of variation of study variable y. The expressions for bias, mean squared error (MSE), and minimum mean squared error (MMSE) of the proposed family of estimators are derived up to the first degree of approximation. In addition, a numerical example and a simulation study are presented to explain the performance of the proposed estimators. It was shown that the proposed estimators perform better compared to all other relevant estimators.

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Transformed ratio type estimators for the population mean in the presence of nonresponse

Cited by 83 publications

References 3 publications

Some Estimation Procedures in Presence of Non-Response in Two-Phase Sampling

Some Estimation Procedures in Presence of Non-Response in Two-Phase Sampling

Finite Population Mean Estimation through a Two-Parameter Ratio Estimator Using Auxiliary Information in Presence of Non-Response

An Efficient General Family of Estimators for Population Mean in the Presence of Non-Response

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