Rcpp::Rcout, and restricted the shared
library's symbol visibility to the registered entry points.First release of FusionForests.
FusionForest() is a Bayesian tree ensemble for combining data from a
randomised controlled trial (RCT) and real-world data (RWD).
The outcome (continuous, or log survival time) is decomposed over separate tree forests: a control forest, a treatment forest, a deconfounding forest and a deviation forest that captures how the treatment effect in the RWD deviates from the RCT. The observational data are not assumed to be unconfounded.
Continuous, right-censored and interval-censored outcomes are
supported via an accelerated failure time formulation, with Gaussian
or Dirichlet-process mixture error distributions (error_dist).
fusion_estimand() — posterior draws of causal survival estimands:
survival difference and acceleration factor.fusion_projection() — interpretable linear projections of the
posterior treatment effect surface.print() and summary() methods for FusionForest fits.SimpleBART() — single-forest BART.SimpleBCF() — Bayesian causal forest with prognostic and treatment
forests.The single-study causal and survival models from the
ShrinkageTrees
package (ShrinkageTrees(), HorseTrees(), CausalShrinkageForest(),
CausalHorseForest(), SurvivalBART(), SurvivalDART(),
SurvivalBCF(), SurvivalShrinkageBCF()) are re-exported, so
library(FusionForests) provides every model from the accompanying
paper in one namespace.