tidy.marginaleffects | R Documentation |
marginaleffects
objectTidy a marginaleffects
object
## S3 method for class 'marginaleffects' tidy(x, conf_level = NULL, ...)
x |
An object produced by the |
conf_level |
numeric value between 0 and 1. Confidence level to use to build a confidence interval. The default |
... |
Additional arguments are passed to the |
The tidy
function calculates average marginal effects by taking the mean
of all the unit-level marginal effects computed by the marginaleffects
function.
The standard error of the average marginal effects is obtained by taking the mean of each column of the Jacobian. . Then, we use this "Jacobian at the mean" in the Delta method to obtained standard errors.
In Bayesian models (e.g., brms
), we compute Average Marginal
Effects by applying the mean function twice. First, we apply it to all
marginal effects for each posterior draw, thereby estimating one Average (or
Median) Marginal Effect per iteration of the MCMC chain. Second, we take
the mean
and quantile
function to the results of Step 1 to obtain the
Average (or Median) Marginal Effect and its associated interval.
A "tidy" data.frame
of summary statistics which conforms to the
broom
package specification.
Other summary:
glance.marginaleffects()
,
reexports
,
summary.comparisons()
,
summary.marginaleffects()
,
summary.marginalmeans()
,
summary.predictions()
,
tidy.comparisons()
,
tidy.deltamethod()
,
tidy.marginalmeans()
,
tidy.predictions()
mod <- lm(mpg ~ hp * wt + factor(gear), data = mtcars) mfx <- marginaleffects(mod) # average marginal effects tidy(mfx)
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