Regression-Type Estimation of a Finite Population Mean in Two-Phase Sampling Using Auxiliary Variable and Attribute

PA Patel; Fagun  Shah

doi:10.3329/jsr.v55i2.58811

Regression-Type Estimation of a Finite Population Mean in Two-Phase Sampling Using Auxiliary Variable and Attribute

Authors

PA Patel Department of Statistics, Sardar Patel University, Vallabh Vidhyanagar 388 120
Fagun Shah Department of Statistics, Sardar Patel University, Vallabh Vidhyanagar 388 120

DOI:

https://doi.org/10.3329/jsr.v55i2.58811

Keywords:

Attribute; auxiliary variables; bias; MSE; optimum estimation; empirical study; simulation; two-phase sampling

Abstract

In this paper, by making regression adjustment, a class of estimators of the finite population mean under two-phase sampling is suggested which incorporates auxiliary information on quantitative and qualitative variables. Making approximation up to first order, bias and mean squared error (MSE) are obtained. A few particular cases of the estimators are discussed. The numerical and empirical comparisons of these estimators with ordinary ratio and regression estimators are carried out using a Monte Carlo simulation.

Journal of Statistical Research 2021, Vol. 55, No. 2, pp. 377-393

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Published

2022-03-30

How to Cite

Patel, P., & Shah, F. . (2022). Regression-Type Estimation of a Finite Population Mean in Two-Phase Sampling Using Auxiliary Variable and Attribute. Journal of Statistical Research, 55(2), 377–393. https://doi.org/10.3329/jsr.v55i2.58811