Estimation of mean vector in presence of non-response

Tripathi, Trivendra; Khare, B. B.

doi:10.1080/03610929708832045

Cited by 15 publications

(8 citation statements)

References 2 publications

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“…In order to reduce the effect of nonresponse in estimation of population mean, Hansen and Hurwitz (1946) gave a technique of sub-sampling of the non-responding group. Following Hansen and Hurwitz (1946) technique, several authors including Cochran (1977), Tripathi and Khare (1997), Tabasum and Khan (2004) and Singh and Kumar (2010 a, b) have contributed towards the improvement of the estimation procedures of population mean in presence of non-response using information on auxiliary variable. In many situations, information on the auxiliary variable may be readily available on all the units of the population; for example, tonnage (or seat capacity) of each vehicle or ship is known in survey sampling of transportation and number of beds in different hospitals may be known in hospital surveys.…”

Section: Introductionmentioning

confidence: 99%

“…denoted by U would not respond on the first call at the second phase but will respond on the second call. Further, we assume that the strata sizes of 1 N and 2 N units are not known well in advance, see Tripathi and Khare (1997). The stratum weights of responding and non-responding groups are given by If non -response occurs on the study variable y as well as on the auxiliary variable x in the second phase sample, the estimators 1 t and 2 t may be considered in the following form as…”

Section: Introductionmentioning

confidence: 99%

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Estimation of population median in presence of non - response under two - phase sampling

Bandyopadhyay¹,

Singh

Das³

2016

Sri Lankan J App Stats

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The present investigation deals with the problem of estimation of population median in presence of non-response under two-phase (double) sampling. Using information on two auxiliary variables, four general classes of estimators have been suggested for four different realistic situations of nonresponses. It is shown that several estimators can be generated from our proposed classes of estimators. Proposed classes of estimators are compared with some contemporary estimators of population median under the similar realistic situations. The merits of the proposed strategies have been interpreted through empirical studies carried over three natural populations and one artificially generated population data sets. This establishes effectiveness of the suggested classes of estimators. Suitable recommendations to the survey statistician have been made.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of population median in presence of non - response under two - phase sampling

Bandyopadhyay¹,

Singh

Das³

2016

Sri Lankan J App Stats

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“…In the case of nonresponse for simple random sampling, Tripathi and Khare (1997) considered the estimation of mean vector for partial and complete nonresponse. Khare and Sinha (2009) proposed two classes of estimators of mean in the presence of non-response using multi-auxiliary variables.…”

Section: Introductionmentioning

confidence: 99%

Generalized Class of Mean Estimators for Two Phase Sampling in the Presence of Nonresponse

Ahmad

Zafar

Bano

2013

JJSS

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A lot of work has been done in two-phase sampling for estimating the population mean of a study variable while considering the non-response at the second phase, see e.g. Khare and Srivastava (1993, 1995), Tabasum and Khan (2004), Singh and Kumar (2008) and Singh et al. (2010). Most authors have used information of a single auxiliary variable while estimating the mean of the study variable, whereas in a practical situation we may require/have auxiliary information on multiple characters. Khare and Sinha (2009, 2011) have used multi-auxiliary characters to estimate the population mean in the presence of nonresponse in the case of simple random sampling. In two-phase sampling, when auxiliary information is obtained at both phases, the nonresponse may occur at both phases as well. In this paper we have proposed a generalized class of estimators for estimating the population mean of a study variable under a two-phase sampling scheme using multi-auxiliary variable(s) in the presence of nonresponse at both phases. The information on all auxiliary variable(s) is not known for the population. The bias and mean square error have been derived for the suggested class. Special cases of the class have also been identified. An empirical study has been conducted for comparing the efficiency of the proposed estimators with a modified version of existing ones.

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“…The technique consists of selecting a sub-sample of non-respondents and the data are collected through specialized efforts from the non-respondents so as to obtain an estimate of non-responding units in the population. Tripathi and Khare (1997) extended the subsampling of non-respondents approach to multivariate case. Okafor (2001Okafor ( , 2005 further extended the approach in the context of element sampling and twostage sampling respectively on two successive occasions.…”

Section: Introductionmentioning

confidence: 99%

Estimation of population mean in two– stage sampling under a deterministic response mechanism in the presence of non-response

Devi¹,

Sisodia²

2017

JANS

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Abstract:In the present paper, we have considered the problem of estimation of population mean in the presence of non-response under two-stage sampling. Two different models of non-response with deterministic response mechanism have been discussed in the paper. The estimators under two non-response models have been developed by using Hansen and Hurwitz (1946) technique. The expressions for the variances and estimates of variance of these estimators have been derived. The optimum values of sample sizes have been obtained by considering a suitable cost function for a fixed variance. A limited simulation study has been carried out to examine the magnitude of percent relative loss (% RL) in standard error due to non-response. An empirical study with the real populations has also been carried out to assess the % RL in standard error due to non-response.

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Estimation of mean vector in presence of non-response

Cited by 15 publications

References 2 publications

Estimation of population median in presence of non - response under two - phase sampling

Estimation of population median in presence of non - response under two - phase sampling

Generalized Class of Mean Estimators for Two Phase Sampling in the Presence of Nonresponse

Estimation of population mean in two– stage sampling under a deterministic response mechanism in the presence of non-response

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