Validation of Estimates of Treatment Effects in Observational Data

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Documentation for package ‘RCTrep’ version 1.2.0

• 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