NEWS

bartCause 1.0-10 (2025-12-11)

Generics that accept ... arguments but do not use them will now issue warnings when called with unknown arguments. Suggestion thanks to Joshua Bon.

Treatment and propensity score (when applicable) are now added to parametric model. Thanks to Joshua Bon for noticing their absence.

bartc now accepts a seed argument that yields reproducible results, even when running with multiple threads and multiple chains.
New parametric argument to bartc allows for arbitrary linear and multilevel models. Requires the stan4bart package to be installed.

Now works with response models in "tmle" and "p.weight" when p.scoreAsCovariate is FALSE.
Correctly summarizes the number of samples when n.chains = 1.
sumamry now correctly computes variance expansion for PATE with weighted observations.
summary correctly drops observations from averages when common support rules are being used. Bug report thanks to Marcela Veselkova.

predict now accepts as options "mu" and "y" for when the user-supplied newdata object already has a valid treatment assignment.

Default type argument for predict is now "mu".
bartc argument crossvalidateBinary renamed to crossvalidate. Accepts one of TRUE, FALSE, "trt", or "rsp". This feature is experimental and discouraged from use.
Confounder expressions that can evaluate successfully in the calling environment but yield a warning are now treated as if they threw an error.
summary for models fit with group.effects as TRUE will use the level names of the grouping factor when reporting the sub-group estimates.

"ite", "sate", "y.0", and "y.1" for generics now returns correctly. Report thanks to Bryan Keller.

Confounders can be passed in as literals when using data argument. This can be of assistance in using complicated formulae with many variables.