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:
call
how bartc
was called
method.rsp
character string specifying the method used to fit the response surface
method.trt
character string specifying the method used to fit the treatment assignment mechanism
ci.info
a named list with items target
, ci.style
, ci.level
, and
pate.style
as passed to summary
n.obs
total number of observations
n.samples
number of samples within any one chain
n.chains
total number of chains
commonSup.rule
common support rule used when fitting object to produce estimates
estimates
a 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.