Difference in difference + IPW + external control borrowing
Usage
DID_EC_IPW(
data,
outcome_col_name,
trial_status_col_name,
treatment_col_name,
covariates_col_name,
T_cross,
model_form_piS = "",
model_form_piA = "",
Bootstrap = FALSE,
R = 500,
bootstrap_CI_type = "bca",
alpha = 0.05,
quiet = TRUE
)Arguments
- data
A data frame containing all subject-level data.
- outcome_col_name
Character vector of outcome column names.
- trial_status_col_name
Name of the trial status column.
- treatment_col_name
Name of the treatment column.
- covariates_col_name
Character vector of covariate column names.
- T_cross
Integer crossover time point.
- model_form_piS
Formula string for the trial participation model.
- model_form_piA
Formula string for the treatment assignment model.
- Bootstrap
Logical. Whether to use bootstrap inference.
- R
Number of bootstrap replicates.
- bootstrap_CI_type
Type of bootstrap CI (e.g.
"bca","perc").- alpha
Significance level.
- quiet
Logical. If
TRUE, suppress printed output.