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) .


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install.packages("noncomplyR")

1.0 by Scott Coggeshall, a year ago


Browse source code at https://github.com/cran/noncomplyR


Authors: Scott Coggeshall [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports MCMCpack, stats

Suggests knitr


See at CRAN