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The couplr package provides high-level functions for optimal one-to-one matching between two groups in R. It addresses direct covariate matching without requiring intermediate propensity score modeling, making it useful for causal inference, experimental design, resource allocation, and image processing tasks.

The package offers two main matching functions: match_couples() for optimal matching with automatic preprocessing, multiple scaling methods, distance constraints, and blocking support; and greedy_couples() for fast approximate matching using sorted, row-best, or priority queue strategies (10-100x faster for large datasets). Use match_couples() for n < 5,000 where guaranteed optimality matters; switch to greedy_couples() for larger datasets prioritizing speed.

Balance diagnostics are built-in via balance_diagnostics() for assessing covariate balance using standardized differences, variance ratios, and KS tests, along with balance_table() for publication-ready output. For lower-level control, lap_solve() provides an interface to 18 linear assignment algorithms with automatic method selection, plus batch solving and K-best solutions via Murty’s algorithm.

Available on CRAN under MIT license.

install.packages("couplr")

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