Represent observed causal data — data

data_observed combines the observed dataframe with specific identification of the columns corresponding to the exposure, outcome, and confounders. It is an essential input of the multibias_adjust() function.

Usage

data_observed(data, bias, exposure, outcome, confounders = NULL)

Arguments

data: Dataframe for bias analysis.
bias: String type(s) of bias distorting the effect of the exposure on the outcome. Can choose from a subset of the following: "uc", "em", "om", "sel". These correspond to uncontrolled confounding, exposure misclassification, outcome misclassification, and selection bias, respectively.
exposure: String name of the column in data corresponding to the exposure variable.
outcome: String name of the column in data corresponding to the outcome variable.
confounders: String name(s) of the column(s) in data corresponding to the confounding variable(s).

Value

An object of class data_observed containing:

data: A dataframe with the selected columns
bias: The type(s) of bias present
exposure: The name of the exposure variable
outcome: The name of the outcome variable
confounders: The name(s) of the confounder variable(s)

Examples

df <- data_observed(
  data = df_sel,
  bias = "uc",
  exposure = "X",
  outcome = "Y",
  confounders = c("C1", "C2", "C3")
)