Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Single Phase Sampling

In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error are derived. An empirical study is given to compare the performance of the estimator with existing estimators. It has been found that the ratio-cum-product estimator using multiple auxiliary attributes is more efficient than mean per unit, product and ratio estimators using one auxiliary attribute, and Product and Ratio estimators using multiple auxiliary attributes in single phase sampling.