Family of Estimators for Estimating Population Median using Auxiliary Information in Survey Sampling
DOI:
https://doi.org/10.13052/jrss0974-8024.1824Keywords:
Auxiliary variable, bias, mean square error, median, simple random sampling, study variableAbstract
In this article, we propose a new family of estimators for estimating the unknown population median of a study variable by utilizing auxiliary information under simple random sampling. The choice of the median, as opposed to the mean, is particularly advantageous in the presence of outliers or skewed distributions, where the mean may be unduly influenced. We derive the expressions for the bias and mean square error (MSE) of the proposed class of estimators up to the first order of approximation. Furthermore, we examine several notable subclasses within the proposed family and calculate their respective MSEs. To assess the efficiency and robustness of the proposed estimators, an empirical study is conducted using real-world data and benchmarked against existing estimators from the literature. The results of this empirical analysis demonstrate that the proposed estimators achieve lower MSEs, underscoring their practical relevance and effectiveness in survey sampling applications.
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