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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>.
| Version: | 1.0 |
| Imports: | MCMCpack (≥ 1.4.0), stats |
| Suggests: | knitr |
| Published: | 2017-08-24 |
| Author: | Scott Coggeshall [aut, cre] |
| Maintainer: | Scott Coggeshall <sscogges at uw.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | noncomplyR results |
| Reference manual: | noncomplyR.pdf |
| Vignettes: |
Introduction to noncomplyR |
| Package source: | noncomplyR_1.0.tar.gz |
| Windows binaries: | r-devel: noncomplyR_1.0.zip, r-release: noncomplyR_1.0.zip, r-oldrel: noncomplyR_1.0.zip |
| macOS binaries: | r-release (arm64): noncomplyR_1.0.tgz, r-oldrel (arm64): noncomplyR_1.0.tgz, r-release (x86_64): noncomplyR_1.0.tgz, r-oldrel (x86_64): noncomplyR_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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