aamatch-package: Artless Automatic Multivariate Matching for Observational...
In aamatch: Artless Automatic Multivariate Matching for Observational Studies
aamatch-package R Documentation
Artless Automatic Multivariate Matching for Observational
Studies
Description
Implements a simple version of multivariate matching using a propensity score, near-exact matching, near-fine balance, and robust Mahalanobis distance matching (Rosenbaum 2020 <doi:10.1146/annurev-statistics-031219-041058>). You specify the variables, and the program does everything else.
Details
Package aamatch implements a simple version of multivariate matching in observational studies, using propensity scores, minimum distance matching, near-exact matching and fine balance. The only function in the package is artless().
Author(s)
Paul Rosenbaum [aut, cre]
Maintainer: Paul Rosenbaum <rosenbaum@wharton.upenn.edu>
References
Rosenbaum, P. R. (2020a) <doi:10.1007/978-3-030-46405-9> Design of Observational Studies (2nd Edition). New York: Springer.
Rosenbaum, P. R. (2020b). <doi:10.1146/annurev-statistics-031219-041058> Modern algorithms for matching in observational studies. Annual Review of Statistics and Its Application, 7(1), 143-176.
Rosenbaum, P. R. (2025) Introduction to the Theory of Observational Studies.
New York: Springer.
Zhang, B., D. S. Small, K. B. Lasater, M. McHugh, J. H. Silber, and P. R. Rosenbaum (2023) <doi:10.1080/01621459.2021.1981337> Matching one sample according to two criteria in observational studies. Journal of the American Statistical Association, 118, 1140-1151.
aamatch documentation built on June 25, 2025, 1:08 a.m.
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| aamatch-package | R Documentation |
Artless Automatic Multivariate Matching for Observational Studies
Description
Implements a simple version of multivariate matching using a propensity score, near-exact matching, near-fine balance, and robust Mahalanobis distance matching (Rosenbaum 2020 <doi:10.1146/annurev-statistics-031219-041058>). You specify the variables, and the program does everything else.
Details
Package aamatch implements a simple version of multivariate matching in observational studies, using propensity scores, minimum distance matching, near-exact matching and fine balance. The only function in the package is artless().
Author(s)
Paul Rosenbaum [aut, cre]
Maintainer: Paul Rosenbaum <rosenbaum@wharton.upenn.edu>
References
Rosenbaum, P. R. (2020a) <doi:10.1007/978-3-030-46405-9> Design of Observational Studies (2nd Edition). New York: Springer.
Rosenbaum, P. R. (2020b). <doi:10.1146/annurev-statistics-031219-041058> Modern algorithms for matching in observational studies. Annual Review of Statistics and Its Application, 7(1), 143-176.
Rosenbaum, P. R. (2025) Introduction to the Theory of Observational Studies. New York: Springer.
Zhang, B., D. S. Small, K. B. Lasater, M. McHugh, J. H. Silber, and P. R. Rosenbaum (2023) <doi:10.1080/01621459.2021.1981337> Matching one sample according to two criteria in observational studies. Journal of the American Statistical Association, 118, 1140-1151.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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