Calculate average adjusted predictions by taking the mean of all the unit-level adjusted predictions computed by the predictions function.

# S3 method for predictions
tidy(x, conf_level = 0.95, ...)

Arguments

x

An object produced by the predictions function.

conf_level

numeric value between 0 and 1. Confidence level to use to build a confidence interval.

...

Additional arguments are passed to the predict() method supplied by the modeling package.These arguments are particularly useful for mixed-effects or bayesian models (see the online vignettes on the marginaleffects website). Available arguments can vary from model to model, depending on the range of supported arguments by each modeling package. See the "Model-Specific Arguments" section of the ?marginaleffects documentation for a non-exhaustive list of available arguments.

Value

A "tidy" data.frame of summary statistics which conforms to the broom package specification.

Examples

mod <- lm(mpg ~ hp * wt + factor(gear), data = mtcars)
mfx <- predictions(mod)
tidy(mfx)
#>    estimate std.error statistic p.value conf.low conf.high
#> 1: 20.09062 0.3837791  52.34945       0 19.33843  20.84282