CRAN

noncomplyR 1.0

Bayesian Analysis of Randomized Experiments with Non-Compliance

Released Aug 24, 2017 by Scott Coggeshall

This package cannot yet be used with Renjin it depends on other packages which are not available: MCMCpack 1.4-3

Dependencies

MCMCpack 1.4-3

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) .

Source

R

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