A family of estimators of population mean using auxiliary information in stratified sampling

This article suggests a family of estimators of population mean using auxiliary information in stratified sampling. The bias and mean-squared error of the suggested family of estimators are derived under large sample approximation. Asymptotic optimum estimator (AOE) in the class of estimators is investigated with its mean-squared error formula. It is identified that the usual unbiased estimator (y) over bar (st), traditional combined ratio estimator (y) over bar (RC), traditional combined regression estimator (y) over bar (lrc), Kadilar and Cingi (2005) estimator (y) over bar (KC), and Shabbir and Gupta (2006) estimator (y) over bar (SG) are particular members of a suggested family of estimators. The new expressions of bias and a mean-square error of Kadilar and Cingi (2005) estimator (y) over bar (KC) and a new expression of a mean-square error of Shabbir and Gupta (2006) estimator (y) over bar (SG) have been derived. Both theoretical and empirical findings are encouraging and support the soundness of the present study.