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

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Articles