Abstract
This paper introduces the concept of calibration estimators to Statistical Regression Estimation and proposes a multivariate calibration regression (M-REG) estimator of population mean in stratified random sampling. It develops a new approach to variance estimation that is more efficient in estimating populations with multiple auxiliary variables using the principle of analysis of variance (ANOVA). The relative performance of the new variance estimation method with respect to the estimation of variance of the proposed M-REG estimator is compared empirically with a corresponding global variance estimation method. Analysis and evaluation presented, proved the dominance of the suggested new approach to variance estimation.
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