Compromise Allocation for Mean Estimation in Stratified Random Sampling Using Auxiliary Attributes When Some Observations are Missing
Sidra Naz, Yousaf Shad Muhammad, Javid Shabbir

Abstract
This paper considers the estimation of ratio of population mean when some observations on study variable and auxiliary variables are missing in the case of stratified random sampling. Four estimator are presented and their bias and mean square error are formulated. Here the problem of stratified random sampling in the case of missing observations for nonlinear random cost with certain probability has been formulated .The formulated problem minimize the coefficient of variation and determines the best compromise allocation.

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