Efficient combination of various estimators in the presence of non-response

The issue of non-response is a common phenomenon in sample surveys. Therefore, there is a need to develop ways of dealing with the challenge whenever it occurs. The current paper first introduces the stratification of the population as a result of the non-response. A theoretical review of the basic non response in sampling is as well explained and derived. The condition that leads to the first non-response estimator as proposed by the Hansen and Hurwitz. The resampling scheme for the non-response adjustment was described. This forms the bases for the new model which proposes a modified ratio estimator of the finite population mean in the presence of non-response when the population median of the auxiliary variable is known. The properties of the proposed estimators are derived and theoretically compared with existing ones. A theoretical efficiency comparison shows that the proposed estimator performs better than the existing ones. Further, the simulated numerical comparison shows that the Bias of the proposed estimator performs better, while its Mean squared error is competitive. Towards, the conclusion of the study we recommend further studies on the band with that balance the impact on the estimator in terms of the variance and the bias. Further, an exponential ratio form of the proposed estimator was recommended to be studied and its properties be examined.

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“…Assuming the non-response in on the study variable only [11]. The suggested modification of the estimator 3 is defined as;…”

Section: Proposed Estimatormentioning

confidence: 99%

Estimation of Finite Population Mean Using Ratio Estimator Based on Known Median of Auxiliary Variable in the Presence of Non-Response

Nderitu¹,

Imboga²,

Wanjoya³

2022

AJTAS

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“…It is quite understandable that estimator with more efficiency can be established by using auxiliary information. Recently, Pal and Singh [2,3], Singh and Usman [4] have developed an efficient estimator for estimation of population mean to handle sub-sampling of nonrespondents as introduced by Hansen and Hurwitz [1]. Bhat et al [5] presented the estimation of population variance in the presence of nonresponse utilizing the linear combination of coefficient of skewness and quartiles as auxiliary information.…”

Section: Introductionmentioning

confidence: 99%

General Parameters Estimation in the Presence of Nonresponse Using Difference-cum Exponential Estimators

Alabi

Peter²,

Oluwafunminiyi³

et al. 2022

ARJOM

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Non response is a common problem in a survey process. Therefore, it is necessary to find a way out of handling non response whenever arises. The current study proposed difference-cum exponential ratio-type estimator for estimation of general parameters using auxiliary information which is defined in two situations of non response. A conventional estimator t*(a,b) is used to define population constants including population mean, standard deviation, coefficient of variation and mean square. The expression of bias and mean square error of the proposed estimators are obtained up to the first order of approximation for situation I and situation II. To compare the efficiency of the proposed estimators over the existing ones, an empirical study is carried out using real and simulated data sets. Both the theoretical and empirical study shows that the proposed class of estimators outperformed other existing estimators.

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“…After the significant contributions of these studies, Yunusa and Kumar [17], Dansawad [18], Singh and Usman [19], Pal and Singh [20,21], Yadav et al [22], Sinha and Kumar [23], Pal and Singh [24], Kumar and Kumar [25], Sanaullah et al [26] and Javaid et al [27] have proposed exponential type estimators for the population mean for Case I.…”

Section: Introductionmentioning

confidence: 99%

“…After Singh et al [16], Kumar and Bhougal [28], Kumar [29], Yadav et al [22], Pal and Singh [20], Singh and Usman [19], Ünal and Kadilar [30,31], Muneer et al [32], Sanaullah et al [26], Riaz et al [33], Sinha and Kumar [23], Pal and Singh [24], Kumar and Kumar [25] and Sanaullah et al [26] also proposed new estimators, taking advantage of an exponential function for Case II.…”

Section: Introductionmentioning

confidence: 99%

A New Family of Exponential Type Estimators in the Presence of Non-Response

Ünal

Kadılar

2021

J. Math. Fund. Sci.

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We propose families of estimators for the population mean using an exponential function in case of non-response. This situation is examined under two cases, Case I and II. The bias, MSE and minimum MSE are separately obtained for both cases. We compare the proposed estimators theoretically with the main estimators from the literature, such as Hansen and Hurwitz (1946), ratio, regression and exponential estimators. The conditions for which the proposed estimators are most efficient are obtained. Moreover, different empirical studies are conducted to support the theoretical results for both cases.

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Efficient combination of various estimators in the presence of non-response

Cited by 8 publications

References 15 publications

Estimation of Finite Population Mean Using Ratio Estimator Based on Known Median of Auxiliary Variable in the Presence of Non-Response

Estimation of Finite Population Mean Using Ratio Estimator Based on Known Median of Auxiliary Variable in the Presence of Non-Response

General Parameters Estimation in the Presence of Nonresponse Using Difference-cum Exponential Estimators

A New Family of Exponential Type Estimators in the Presence of Non-Response

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