Package: noncomplyR
Type: Package
Title: Bayesian Analysis of Randomized Experiments with Non-Compliance
Version: 1.0
Date: 2017-07-25
Authors@R: person("Scott", "Coggeshall", email = "sscogges@uw.edu", role = c("aut", "cre"))
Author: Scott Coggeshall [aut, cre]
Maintainer: Scott Coggeshall <sscogges@uw.edu>
Description: 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>.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
Imports: MCMCpack (>= 1.4.0), stats
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-08-24 00:29:31 UTC; sscogges
Repository: CRAN
Date/Publication: 2017-08-24 08:30:38 UTC
Built: R 4.6.0; ; 2026-04-26 09:08:29 UTC; unix
