Open Access Open Access  Restricted Access Subscription or Fee Access

Estimation of Population Mean in the Presence of Nonresponse and Measurement Errors Under Double Sampling for Stratification

Onyango O. Ronald, Oduor Brian, Odundo Francis

Abstract



The present study addresses the problem of estimation of the finite population mean in the presence of nonresponse and measurement errors under double sampling for stratification. In the literature, nonresponse and measurement errors have been studied independently under double sampling for stratification. A generalized estimator of the population mean that utilizes information on a single auxiliary variable is proposed. The expression for the bias and mean square error of the proposed generalized estimator are obtained for the fixed sample size and cost up to the first order of approximation. The unbiased version of the proposed generalized estimator is developed and the minimum variance is derived. The cost of the survey is studied theoretically. The numerical study reveals that the optimum estimator is more efficient than other existing estimators.

Keywords


Double sampling for stratification, population mean, nonresponse, measurement errors, and optimal allocation

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.