Package: RIIM
Type: Package
Title: Randomization-Based Inference Under Inexact Matching
Version: 2.0.0
Authors@R: c(person(given = "Jianan",
                    family = "Zhu",
                    role = c("aut", "cre"),
                    email = "jz4698@nyu.edu"),
             person(given = "Jeffrey",
                    family = "Zhang",
                    role = "aut"),
             person(given = "Zijian",
                    family = "Guo",
                    role = "aut"),
             person(given = "Siyu",
                    family = "Heng",
                    role = "aut"))
Description: Randomization-based inference for average treatment effects in potentially inexactly matched observational studies. It implements the inverse post-matching probability weighting framework proposed by the authors. The post-matching probability calculation follows the approach of Pimentel and Huang (2024) <doi:10.1093/jrsssb/qkae033>. The optimal full matching method is based on Hansen (2004) <doi:10.1198/106186006X137047>. The variance estimator extends the method proposed in Fogarty (2018) <doi:10.1111/rssb.12290> from the perfect randomization settings to the potentially inexact matching case. Comparisons are made with conventional methods, as described in Rosenbaum (2002) <doi:10.1007/978-1-4757-3692-2>, Fogarty (2018) <doi:10.1111/rssb.12290>, and Kang et al. (2016) <doi:10.1214/15-aoas894>. 
Imports: MASS, xgboost, optmatch
Suggests: VGAM, mvtnorm
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-03-10 20:45:40 UTC; jiananzhu
Author: Jianan Zhu [aut, cre],
  Jeffrey Zhang [aut],
  Zijian Guo [aut],
  Siyu Heng [aut]
Maintainer: Jianan Zhu <jz4698@nyu.edu>
Repository: CRAN
Date/Publication: 2025-03-12 17:40:05 UTC
Built: R 4.6.0; ; 2025-11-13 04:49:53 UTC; windows
