noncomplyR: Bayesian Analysis of Randomized Experiments with Non-Compliance
Version 1.0

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) .

Package details

AuthorScott Coggeshall [aut, cre]
Date of publication2017-08-24 08:30:38 UTC
MaintainerScott Coggeshall <[email protected]>
LicenseGPL-2
Version1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("noncomplyR")

Try the noncomplyR package in your browser

Any scripts or data that you put into this service are public.

noncomplyR documentation built on Aug. 24, 2017, 9:02 a.m.