data_validation {multibias} | R Documentation |
data_validation
combines the validation dataframe with specific
identification of the appropriate columns for bias adjustment, including:
true exposure, true outcome, confounders, misclassified exposure,
misclassified outcome, and selection. The purpose of validation data is to
use an external data source to transport the necessary causal relationships
that are missing in the observed data.
data_validation(
data,
true_exposure,
true_outcome,
confounders = NULL,
misclassified_exposure = NULL,
misclassified_outcome = NULL,
selection = NULL
)
data |
Dataframe of validation data |
true_exposure |
String name of the column in |
true_outcome |
String name of the column in |
confounders |
String name(s) of the column(s) in |
misclassified_exposure |
String name of the column in |
misclassified_outcome |
String name of the column in |
selection |
String name of the column in |
df <- data_validation(
data = df_sel_source,
true_exposure = "X",
true_outcome = "Y",
confounders = c("C1", "C2", "C3"),
selection = "S"
)