Abstract
In this article, a combined general family of estimators is proposed for estimating finite population mean of a sensitive variable in stratified random sampling with non-sensitive auxiliary variable based on randomized response technique. Under stratified random sampling without replacement scheme, the expression of bias and mean square error (MSE) up to the first-order approximations are derived. Theoretical and empirical results through a simulation study show that the proposed class of estimators is more efficient than the existing estimators, i.e., usual stratified random sample mean estimator, Sousa et al (2014) ratio and regression estimator of the sensitive variable in stratified sampling.
Highlights
It is common practice in sample survey related to agriculture, market, industries, and social research, and so forth that usually more than one characteristic is observed from each sampled unit of population
The main goal is to propose a combined general family of estimators for estimating the finite population mean of a sensitive variable in stratified random sampling with non-sensitive auxiliary variable based on randomized response technique
This paper suggests a combined general family of estimators of population mean of a sensitive variable using non-sensitive auxiliary information, using RRT methodology (Warner 1965; Gupta et al 2002 and 2010) in stratified random sampling
Summary
It is common practice in sample survey related to agriculture, market, industries, and social research, and so forth that usually more than one characteristic is observed from each sampled unit of population. Many authors have discussed ratio and regression estimators when both Y and X are directly observable These include Kadilar and Cingi (2003), Shabbir and Gupta (2005), and Nangsue (2009). Gupta and shabbir (2008) have suggested a general class of ratio estimators when the population parameters of the auxiliary variable are known. These estimators have been extended by kadilar and Cingi (2003) to stratified random sampling scheme. This paper suggests a combined general family of estimators of population mean of a sensitive variable using non-sensitive auxiliary information, using RRT methodology (Warner 1965; Gupta et al 2002 and 2010) in stratified random sampling. Theoretical and empirical results through a simulation results support the reliability of the present study
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