call_dashboard: Visualizing validation results according to four steps,...

In duolajiang/RCTrep: Validation of Estimates of Treatment Effects in Observational Data

Visualizing validation results according to four steps, namely, set-selection, estimation, diagnosis, and validation

Description

Visualizing validation results according to four steps, namely, set-selection, estimation, diagnosis, and validation

Usage

call_dashboard(source.obj = NULL, target.obj = NULL, source.obj.rep = NULL)

Arguments

source.obj	an instantiated object of class TEstimator. The estimates of conditional average treatment effects are compared to those from target.obj.
target.obj	an instantiated object of class TEstimator. The estimates of conditional average treatment effects are regarded as unbiased of truth.
source.obj.rep	an instantiated object of class SEstimator. The estimates of conditional average treatment effects are compared to those from target.obj.

Value

an interactive interface visualizing results of four steps

Examples

source.data <- RCTrep::source.data[sample(dim(RCTrep::source.data)[1],500),]
target.data <- RCTrep::target.data[sample(dim(RCTrep::target.data)[1],500),]

vars_name <- list(confounders_treatment_name = c("x1","x2","x3","x4","x5","x6"),
                  treatment_name = c('z'),
                  outcome_name = c('y')
)
confounders_sampling_name <- c("x2","x6")

source.obj <- TEstimator_wrapper(
 Estimator = "G_computation",
 data = source.data,
 vars_name = vars_name,
 outcome_method = "glm",
 outcome_form=y ~ x1 + x2 + x3 + z + z:x1 + z:x2 +z:x3+ z:x6,
 name = "RWD",
 data.public = FALSE
)

target.obj <- TEstimator_wrapper(
 Estimator = "Crude",
 data = target.data,
 vars_name = vars_name,
 name = "RCT",
 data.public = FALSE,
 isTrial = TRUE
)

strata <- c("x1","x4")
source.rep.obj <- SEstimator_wrapper(Estimator = "Exact",
                                     target.obj = target.obj,
                                     source.obj = source.obj,
                                     confounders_sampling_name =
                                     confounders_sampling_name)
source.rep.obj$EstimateRep(stratification = strata, stratification_joint = TRUE)

call_dashboard(source.obj = source.obj,
               target.obj = target.obj,
               source.obj.rep = source.obj.rep)

duolajiang/RCTrep documentation built on April 15, 2023, 2:56 a.m.