MrPlew: Locally Equivalent Weights for Multilevel Regression and Poststratification

Ryan Giordano, Alice Cima, Jared Murray, Erin Hartman, and Avi Feller write: Multilevel regression and poststratification (MrP) has become a workhorse method for estimating population quantities from non-probability surveys, and is the primary model-based alternative to traditional survey calibration weighting methods, such as raking. For simple linear regression models, MrP methods admit “equivalent weights”, allowing for direct comparisons between MrP and traditional calibration weighting. Such weights, however, have been unavailable for the most widely used MrP models, such as logistic regression. In this paper, we develop a natural generalization, “MrP locally equivalent weights” (MrPlew), which represent MrP as a weighting-style estimator that is locally equivalent to calibration weights near the observed responses. Cool! This goes beyond my 2007 paper, Struggles with survey weighting and regression modeling (“for logistic regression, the poststratified estimate is no longer a…