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. Uses propensity probabilities
and arm-specific prognostic scores for matching, with a complete quadratic
bias correction in each arm's double score. Provides linearization-based
multinomial replication variance estimates and centered normal Wald
confidence intervals, retaining the original matching reuse coefficients
without re-matching. Supplied scores can be held fixed for inference
conditional on those scores. This weight-only interface does not encode
survey strata, clusters, or design-specific replicate weights.
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