Two new families of estimators for the population mean under stratified random sampling using an auxiliary attribute

The paper addresses the problem of estimating the population mean Y of the study variable Y in the presence of an auxiliary attribute f under stratified random sampling. Two general families of estimators for the population mean, using information on an auxiliary attribute, are proposed in a stratified sampling scheme. The expressions for the bias and mean squared error of the proposed families of estimators have been derived up to the first order of approximation. Optimal conditions are obtained under which the proposed families of estimators have minimum mean squared errors. The families of estimators of Shahzad et al. (2019) and Zaman and Kadilar (2020) are members of the proposed families. A numerical illustration is also provided to support the theoretical findings.