It is vital to assess the heterogeneity of treatment effects (HTE) when making health care decisions for an individual patient or a group of patients. Nevertheless, it remains challenging to evaluate HTE based on information collected from clinical studies that are often designed and conducted to evaluate the efficacy of a treatment for the overall population. The Bayesian framework offers a principled and flexible approach to estimate and compare treatment effects across subgroups of patients defined by their characteristics. This package allows users to explore a wide range of Bayesian HTE analysis models, and produce posterior inferences about HTE. See Wang et al. (2018) <DOI:10.18637/jss.v085.i07> for further details.
|Author||Chenguang Wang [aut, cre], Ravi Varadhan [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R)|
|Maintainer||Chenguang Wang <[email protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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