MDEI: Implementing the Method of Direct Estimation and Inference
Causal and statistical inference on an arbitrary treatment
effect curve requires care in both estimation and inference. This
package, implements the Method of Direct Estimation and Inference as introduced in "Estimation and Inference on Nonlinear and Heterogeneous Effects" by Ratkovic and Tingley (2023) <doi:10.1086/723811>. The method takes an outcome, variable of theoretical interest
(treatment), and set of variables and then returns a partial
derivative (marginal effect) of the treatment variable at each point
along with uncertainty intervals. The approach offers two advances.
First, a split-sample approach is used as a guard against over-fitting.
Second, the method uses a data-driven interval derived from conformal
inference, rather than relying on a normality assumption on the error
||R (≥ 3.6.0)
||grDevices, MASS, ranger, Rcpp (≥ 1.0.6), splines2
||Marc Ratkovic [aut, cre],
Dustin Tingley [ctb],
Nithin Kavi [aut]
||Marc Ratkovic <ratkovic at princeton.edu>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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