Skip to contents

Marginal slopes (partial derivatives) via marginaleffects

Source: R/effects.R
morie_effects_slopes.Rd

Thin extender over marginaleffects::slopes() for continuous marginal effects (Stata-style margins, dydx()).

Usage

morie_effects_slopes(model, variables = NULL, ...)

Arguments

model

A fitted model object.

variables

Character vector of focal variables. When NULL, the marginaleffects default (all continuous predictors) is used.

...

Further arguments forwarded to marginaleffects::slopes().

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_slopes(fit, variables = "x"))
}
#> 
#>  Estimate Std. Error      z Pr(>|z|)   S  2.5 % 97.5 %
#>   -0.0353      0.122 -0.288    0.773 0.4 -0.275  0.205
#>   -0.0353      0.122 -0.288    0.773 0.4 -0.275  0.204
#>   -0.0353      0.122 -0.289    0.773 0.4 -0.275  0.204
#>   -0.0353      0.122 -0.288    0.773 0.4 -0.275  0.204
#>   -0.0353      0.122 -0.289    0.773 0.4 -0.275  0.204
#>   -0.0353      0.122 -0.288    0.773 0.4 -0.275  0.204
#> 
#> Term: x
#> Type: response
#> Comparison: dY/dX
#>