Weighted Double Score Matching for Survey-Weighted Causal Inference R package wdsmatch version 0.1.1 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". Software Depends: R (>= 3.5.0) Imports: stats Suggests: testthat (>= 3.0.0), knitr, rmarkdown Yukang Zeng <ykzeng2019@gmail.com> Comprehensive R Archive Network (CRAN) Yukang Zeng [aut, cre], Guangyu Tong [aut], Jiaqi Tong [aut], Haidong Lu [aut], Bhramar Mukherjee [aut], Fan Li [aut] GPL-3 2026-04-21 application/tgz https://CRAN.R-project.org/package=wdsmatch doi:10.32614/CRAN.package.wdsmatch