Estimation of Finite Population Variance Under Stratified Sampling in the Presence of Measurement Errors

ABSTRACT

Measurement errors may significantly distort the properties of an estimator. In this paper, estimators of the finite population variance using the information on first and second raw moments of the study variable are developed under stratified random sampling that incorporate the variance of a measurement error component. Additionally, combined and separate estimators are also developed for estimating the finite population variance using supplementary information in terms of one or two auxiliary variables. An empirical study is carried out to study the effect of measurement error on the relative efficiencies of the proposed estimators.

KEYWORDS:

• Absolute bias
• auxiliary information
• combined and separate estimators
• relative efficiency
• measurement error
• unbiased estimator

Disclosure statement

No potential conflict of interest was reported by the author(s).