Package: noncomplyR 1.0

noncomplyR: 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) <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>.

Authors:Scott Coggeshall [aut, cre]

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3 exports 0.00 score 10 dependencies 7 scripts 125 downloads

Last updated 7 years agofrom:1a9f8c2b42. Checks:OK: 7. Indexed: yes.

Exports:cacecompliance_chainsummarize_chain

Dependencies:codalatticeMASSMatrixMatrixModelsmcmcMCMCpackquantregSparseMsurvival