# Validation of Estimates of Treatment Effects in Observational Data

## Documentation for package ‘RCTrep’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

call_dashboard | Visualizing validation results according to four steps, namely, set-selection, estimation, diagnosis, and validation
DGM | Generating RCT data or observational data for the examples used in the package
Fusion | Validation of estimates of conditional average treatment effects in objects of class 'TEstimator' and 'SEstimator'.
GenerateSyntheticData | Generating the synthetic RCT data given marginal distribution of each covariate
quasar.agg | Aggregated data derived from paper of QUASAR trial
quasar.obj | An object of class TEstimator_Synthetic using quasar.synthetic
quasar.synthetic | A synthetic QUASAR trial dataset, where outcome is a binary variable, treatment is a binary variable.
RCTREP | Replicate treatment effect estimates obtained from a randomized control trial using observational data
SEstimator_wrapper | Estimating the weighted conditional average treatment effects in 'source.obj' based on input objects 'source.obj' and 'target.obj' of class 'TEstimator'.
source.binary.data | A dataset of simulated observational data, where outcome is binary variable. The data is filtered after compared to target.binary.data
source.data | A data set of simulated observational data, where outcome is continuous variable, treatment is a binary variable.
target.binary.data | A dataset of simulated RCT data, where outcome is binary variable. The data is filtered after compared to source.binary.data
target.data | A data set of simulated RCT data, where outcome is continuous variable, treatment is a binary variable.
TEstimator_wrapper | Estimating conditional average treatment effects