Estimating the population proportion in modified ranked set sampling methods

ABSTRACT

In this paper, proportion estimators and associated variance estimators are proposed for a binary variable with a concomitant variable based on modified ranked set sampling methods, which are extreme ranked set sampling (ERSS), median ranked set sampling (MRSS), percentile ranked set sampling (Per-RSS) and L ranked set sampling (LRSS) methods. The Monte Carlo simulation study is performed to compare the performance of the estimators based on bias, mean squared error, and relative efficiency for different levels of correlation coefficient, set and cycle sizes under normal and log-normal distributions. Moreover, the study is supported with real data application.

KEYWORDS:

• Ranked set sampling
• modified ranked set sampling methods
• proportion estimator
• variance of proportion estimator
• relative efficiency

2010 MATHEMATICS SUBJECT CLASSIFICATION:

• 62D05

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Neslihan Demırel  http://orcid.org/0000-0002-5394-4721