This paper reviews the design-based, model-assisted approach to using data from a complex survey together with auxiliary information to estimate finite population parameters. A general recipe for deriving model-assisted estimators is presented and design-based asymptotic analysis for such estimators is reviewed. The recipe allows for a very broad class of prediction methods, with examples from the literature including linear models, linear mixed models, nonparametric regression and machine learning techniques.
"Model-Assisted Survey Estimation with Modern Prediction Techniques." Statist. Sci. 32 (2) 190 - 205, May 2017. https://doi.org/10.1214/16-STS589