Generalized Regression Estimators with High-Dimensional Covariates.

ABSTRACT: Data from a large number of covariates with known population totals are frequently observed in survey studies. These auxiliary variables contain valuable information that can be incorporated into estimation of the population total of a survey variable to improve the estimation precision. We consider the generalized regression estimator formulated under the model-assisted framework in which a regression model is utilized to make use of the available covariates while the estimator still has basic design-based properties. The generalized regression estimator has been shown to improve the efficiency of the design-based Horvitz-Thompson estimator when the number of covariates is fixed. In this study, we investigate the performance of the generalized regression estimator when the number of covar

SUBMITTER: Ta T 

PROVIDER: S-EPMC7313320 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature