bartcFit ObjectsSummarizes bartc fits by calculating target quantities and uncertainty estimates.
# S3 method for bartcFit
summary(object,
target = c("pate", "sate", "cate"),
ci.style = c("norm", "quant", "hpd"), ci.level = 0.95,
pate.style = c("ppd", "var.exp"),
...)An object of class bartcFit.summary equivalent to a list with named items:
callhow bartc was called
method.rspcharacter string specifying the method used to fit the response surface
method.trtcharacter string specifying the method used to fit the treatment assignment mechanism
ci.infoa named list with items target, ci.style, ci.level, and
pate.style as passed to summary
n.obstotal number of observations
n.samplesnumber of samples within any one chain
n.chainstotal number of chains
commonSup.rulecommon support rule used when fitting object to produce estimates
estimatesa data.frame with columns "estimate" - the target,
"sd" - standard deviation of posterior of estimate,
"ci.lower" - lower bound of credible region,
"ci.upper" - upper bound of credible region,
and optionally "n.cut" - how many observations were dropped using
common support rule
Object of class bartcFit.
Treatment effect to calculate. One of "pate" - population average treatment effect,
"sate" - sample average treatment effect, and "cate" - conditional average
treatment effect.
Means of calculating confidence intervals (posterior credible regions). Options include
"norm" - use a normal approximation, "quant" - the empirical quantites of the
posterior samples, and "hpd" - region of highest posterior density.
Level of confidence for intervals.
For target "pate", calculate uncertainty by using "ppd" - the posterior
predictive distribution or "var.exp" a variance expansion formula.
Not used at moment, but present to match summary generic signature.
Vincent Dorie: vdorie@gmail.com.
summary produces a numeric and qualitative summary of a bartc fit.
Target Types
The SATE and PATE involve calculating predicted response values under different treatment conditions.
When using extract or fitted, these values are simulated directly
from the posterior predictive distribution. However, since these quantities all have the same expected
value, in order to provide consistent results summary only uses those simulations to derive
credible intervals. Thus the estimates for CATE, SATE, and PATE all should be reported as the same
but with increasing degrees of uncertainty.
Grouped Data
If a model is fit with a supplied grouping variable and group.effects = TRUE, the estimates
will also be reported within groups. When possible, the last line corresponds to the population. Within
group estimates for resposne methods such as "tmle" cannot easily be extrapolated to the
population at large - the means will combine based on the sample sizes but the uncertainty estimates
will lack correlations.