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noncomplyR

Bayesian Analysis of Randomized Experiments with Non-Compliance

Functions for Bayesian analysis of data from randomized experiments with non-compliance. The functions are based on the models described in Imbens and Rubin (1997) <doi:10.1214/aos/1034276631>. Currently only two types of outcome models are supported: binary outcomes and normally distributed outcomes. Models can be fit with and without the exclusion restriction and/or the strong access monotonicity assumption. Models are fit using the data augmentation algorithm as described in Tanner and Wong (1987) <doi:10.2307/2289457>.

Versions across snapshots

VersionRepositoryFileSize
1.0 rolling linux/jammy R-4.5 noncomplyR_1.0.tar.gz 58.4 KiB
1.0 rolling linux/noble R-4.5 noncomplyR_1.0.tar.gz 58.4 KiB
1.0 rolling source/ R- noncomplyR_1.0.tar.gz 76.2 KiB
1.0 latest linux/jammy R-4.5 noncomplyR_1.0.tar.gz 58.4 KiB
1.0 latest linux/noble R-4.5 noncomplyR_1.0.tar.gz 58.4 KiB
1.0 latest source/ R- noncomplyR_1.0.tar.gz 76.2 KiB
1.0 2026-04-26 source/ R- noncomplyR_1.0.tar.gz 76.2 KiB
1.0 2026-04-23 source/ R- noncomplyR_1.0.tar.gz 76.2 KiB
1.0 2026-04-09 windows/windows R-4.5 noncomplyR_1.0.zip 64.3 KiB
1.0 2025-04-20 source/ R- noncomplyR_1.0.tar.gz 76.2 KiB

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