<i>kpop</i>: a kernel balancing approach for reducing specification assumptions in survey weighting.

ABSTRACT: With the precipitous decline in response rates, researchers and pollsters have been left with highly nonrepresentative samples, relying on constructed weights to make these samples representative of the desired target population. Though practitioners employ valuable expert knowledge to choose what variables X must be adjusted for, they rarely defend particular functional forms relating these variables to the response process or the outcome. Unfortunately, commonly used calibration weights-which make the weighted mean of X in the sample equal that of the population-only ensure correct adjustment when the portion of the outcome and the response process left unexplained by linear functions of X are independent. To alleviate this functional form dependency, we describe kernel balancing for pop

SUBMITTER: Hartman E 

PROVIDER: S-EPMC12352454 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature