counterfactual: Generate "counterfactual" datasets for use in...
In marginaleffects: Marginal Effects, Marginal Means, Predictions, and Contrasts

Description Usage Arguments Details Value Examples

Generate "counterfactual" datasets for use in marginaleffects's newdata argument

1	counterfactual(..., model = NULL, newdata = NULL)

`...`	named arguments with vectors of values for the variables to construct (see Examples below.)
`model`	Model object
`newdata`	data.frame (one and only one of the `model` and `newdata` arguments must be true).

If counterfactual is used in a marginaleffects or predictions call as the newdata argument, users do not need to specify the model or newdata argument. The data is extracted automatically from the model.

If users supply a model, the data used to fit that model is retrieved using the insight::get_data function.

If users supply a model, the data used to fit that model is retrieved using the insight::get_data function, and then replicated with different values of the variables in the at list.

A data.frame where each row of the original data is repeated multiple times for each of the values of the variables in the at list. See example below.

# All rows are repeated twice, with different values of `hp`
cd <- counterfactual(newdata = mtcars, hp = c(100, 110))
cd[cd$rowid %in% 1:3,]

# We get the same result by feeding a model instead of a data.frame
mod <- lm(mpg ~ hp + wt, mtcars)
cd <- counterfactual(model = mod, hp = c(100, 110))
cd[cd$rowid %in% 1:3,]

# Use in `marginaleffects` to compute "Counterfactual Average Marginal Effects"
marginaleffects(mod, newdata = counterfactual(hp = c(100, 110)))