`plot.clarify_adrf()`

plots the output of `sim_adrf()`

. For the average dose-response function (ADRF, requested with `contrast = "adrf"`

in `sim_adrf()`

), this is a plot of the average marginal mean of the outcome against the requested values of the focal predictor; for the average marginal effects function (AMEF, requested with `contrast = "amef"`

in `sim_adrf()`

), this is a plot of the instantaneous average marginal effect of the focal predictor on the outcome against the requested values of the focal predictor.

## Usage

```
# S3 method for clarify_adrf
plot(
x,
ci = TRUE,
level = 0.95,
method = "quantile",
baseline,
color = "black",
...
)
```

## Arguments

- x
a

`clarify_adrf`

object resulting from a call to`sim_adrf()`

.- ci
`logical`

; whether to display confidence bands for the estimates. Default is`TRUE`

.- level
the confidence level desired. Default is .95 for 95% confidence intervals.

- method
the method used to compute confidence bands. Can be

`"wald"`

to use a Normal approximation or`"quantile"`

to use the simulated sampling distribution (default). See`summary.clarify_est()`

for details. Abbreviations allowed.- baseline
`logical`

; whether to include a horizontal line at`y = 0`

on the plot. Default is`FALSE`

for the ADRF (since 0 might not be in the range of the outcome) and`TRUE`

for the AMEF.- color
the color of the line and confidence band in the plot.

- ...
for

`plot()`

, further arguments passed to`ggplot2::geom_density()`

.

## Details

These plots are produced using `ggplot2::geom_line()`

and `ggplot2::geom_ribbon()`

. The confidence bands should be interpreted pointwise (i.e., they do not account for simultaneous inference).

## See also

`summary.clarify_est()`

for computing p-values and confidence intervals for the estimated quantities.