noncomplyR (1.0)

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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) . 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) .

Maintainer: Scott Coggeshall
Author(s): Scott Coggeshall [aut, cre]

License: GPL-2

Uses: MCMCpack, knitr

Released about 2 years ago.



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