RCTrep - Validation of Estimates of Treatment Effects in Observational
Data
Validates estimates of (conditional) average treatment
effects obtained using observational data by a) making it easy
to obtain and visualize estimates derived using a large variety
of methods (G-computation, inverse propensity score weighting,
etc.), and b) ensuring that estimates are easily compared to a
gold standard (i.e., estimates derived from randomized
controlled trials). 'RCTrep' offers a generic protocol for
treatment effect validation based on four simple steps, namely,
set-selection, estimation, diagnosis, and validation. 'RCTrep'
provides a simple dashboard to review the obtained results. The
validation approach is introduced by Shen, L., Geleijnse, G.
and Kaptein, M. (2023) <doi:10.21203/rs.3.rs-2559287/v1>.