Gradient boosting inside a two-step propensity-score weighting framework improves population estimates from nonprobability samples when selection is nonlinear, but not uniformly over all settings.
First, 10 base covariates (𝑉1, ⋯ , 𝑉7) were generated independently following standard normal distributions
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Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples
Gradient boosting inside a two-step propensity-score weighting framework improves population estimates from nonprobability samples when selection is nonlinear, but not uniformly over all settings.