Estimating causal effects in the presence of post-treatment confounding using principal stratification. 'PStrata' allows for customized monotonicity assumptions and exclusion restriction assumptions, with automatic full Bayesian inference supported by 'Stan'. The main workflow is PStrataModel() to specify the model, fit() to run MCMC sampling, estimate() to extract potential outcomes, and contrast() to compute causal effects. Visualization tools are provided for diagnosis and interpretation. See Liu and Li (2023) <doi:10.48550/arXiv.2304.02740> for details.
Package details |
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| Author | Bo Liu [aut, cre], Fan Li [ctb] |
| Maintainer | Bo Liu <bo.liu1997@gmail.com> |
| License | GPL (>= 2) |
| Version | 1.0.0 |
| URL | https://github.com/LauBok/PStrata |
| Package repository | View on CRAN |
| Installation |
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