On the Estimation of Variance of Calibration Regression Estimators with Multiple Auxiliary Informati

The notion of calibration estimators is introduced to Statistical Regression Estimation in this study, and a multivariate calibration regression (M-REG) estimator of population mean in stratified random sampling is proposed. Using the principle of analysis of variance, it proposes a new approach to variance estimation that is more efficient in estimating populations with several auxiliary variables (ANOVA). The relative performance of the novel variance estimation approach in comparison to the suggested M-REG estimator's variance estimation is empirically tested with a similar global variance estimation approach. The results of the analysis and evaluation demonstrated the superiority of the proposed new methodology to variance estimation.

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