wdsmatch: Weighted Double Score Matching for Survey-Weighted Causal
Inference
Implements weighted double score matching (WDSM) for estimating
population-level causal effects from complex survey data. Combines
propensity scores and prognostic scores with survey design weights for
matching, survey-weighted imputation within match sets, and Hajek
normalization to target the population average treatment effect (PATE) and
the population average treatment effect on the treated (PATT). Supports
both retrospective (treatment-dependent) and prospective
(treatment-independent) sampling designs. Achieves double robustness:
consistent estimation when either the propensity score or prognostic score
model is correctly specified. Provides polynomial sieve bias correction
and linearization-based multinomial bootstrap variance estimation that
preserves the survey-weighted matching structure without re-matching.
Methods are described in Zeng, Tong, Tong, Lu, Mukherjee, and Li
(2026, under review) "Where to weight? Estimating population causal
effects with weighted double score matching in complex surveys".
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