Adjusted predictions via marginaleffects — morie_effects

Thin extender over marginaleffects::predictions() for unit- level or grid-level adjusted predictions.

Usage

morie_effects_predictions(model, newdata = NULL, ...)

Arguments

model: A fitted model object supported by insight / marginaleffects.
newdata: Optional data frame for which to predict. Defaults to the model frame when NULL (the marginaleffects default).
...: Further arguments forwarded to marginaleffects::predictions().

Value

A marginaleffects data frame.

Examples

if (requireNamespace("marginaleffects", quietly = TRUE)) {
  set.seed(1)
  df <- data.frame(y = rnorm(60), x = rnorm(60), g = factor(rep(c("a", "b"), 30)))
  fit <- stats::lm(y ~ x + g, data = df)
  head(morie_effects_predictions(fit))
}
#> 
#>  Estimate Std. Error      z Pr(>|z|)   S   2.5 % 97.5 %
#>    0.1604      0.325  0.493    0.622 0.7 -0.4770  0.798
#>   -0.0206      0.158 -0.130    0.897 0.2 -0.3311  0.290
#>    0.2208      0.174  1.269    0.204 2.3 -0.1202  0.562
#>   -0.0230      0.157 -0.146    0.884 0.2 -0.3315  0.286
#>    0.2713      0.186  1.460    0.144 2.8 -0.0928  0.635
#>   -0.0286      0.157 -0.183    0.855 0.2 -0.3359  0.279
#> 
#> Type: response
#>