Performance evaluation of novel logarithmic estimators under correlated measurement errors

ABSTRACT

In survey research, the issue of measurement errors (ME) has been sorted out by various authors, but the issue of correlated measurement errors (CME) has only been studied by Shalabh and Tsai (2017) till date. This article provides a modest acquaintance to evaluate the performance of few novel logarithmic estimators of population mean in the existence of CME under simple random sampling (SRS). The mean square error of the proposed estimators has been obtained. It has been exhibited theoretically under certain conditions that the proposed class of estimators dominates their conventional counterparts. Furthermore, the theoretical findings have been assessed with a Monte Carlo simulation using a hypothetically gendered population and proper suggestions have been forwarded to the survey professionals.

KEYWORDS:

• Correlated measurement errors
• Monte Carlo simulation
• mean square error

Acknowledgment

The authors are thankful to the anonymous reviewers for their valuable suggestions and to the editor-in-chief.

Disclosure statement

No potential competing interest was reported by the authors.