covariate_table: Create Covariate Balance Table
In katiecoburn/generalizeR: What the Package Does (One Line, Title Case)

This function is designed for use within 'assess().'

covariate_table(
  trial,
  selection_covariates,
  data,
  weighted_table = FALSE,
  selection_method = "lr",
  is_data_disjoint = TRUE
)

`trial`	variable name denoting binary trial participation (1 = trial participant, 0 = not trial participant)
`selection_covariates`	vector of covariate names in data set that predict trial participation
`data`	data frame comprised of "stacked" trial and target population data
`weighted_table`	defaults to FALSE; whether weights are already included and do not need to be estimated
`selection_method`	method to estimate the probability of trial participation. Default is logistic regression ("lr"). Other methods supported are Random Forests ("rf") and Lasso ("lasso")
`is_data_disjoint`	defaults to TRUE. If TRUE, then trial and population data are considered independent. This affects calculation of the weights