Initializes the specification of a CDE estimator based on an augmented inverse probability weighting approach.
Usage
cde_aipw(trim = c(0.01, 0.99), aipw_blip = TRUE)Arguments
- trim
A vector of length 2 indicating what quantiles of the propensity scores should be trimmed. By default this is
c(0.01, 0.99)meaning that the top and bottom 1% of propensity scores are trunctated to these quantiles. If NULL, no trimming occurs.- aipw_blip
If
TRUE(the default), augmented inverse probability weighting estimators will be used to estimate intermediate outcome regressions (blip functions).