`marginal_plot`

allows to visualize prior and
posterior distributions of marginal estimates of a RoBMA regression model.

```
marginal_plot(
x,
parameter,
conditional = FALSE,
plot_type = "base",
prior = FALSE,
output_scale = NULL,
dots_prior = NULL,
...
)
```

- x
a fitted RoBMA regression object

- parameter
regression parameter to be plotted

- conditional
whether conditional marginal estimates should be plotted. Defaults to

`FALSE`

which plots the model-averaged estimates.- plot_type
whether to use a base plot

`"base"`

or ggplot2`"ggplot"`

for plotting. Defaults to`"base"`

.- prior
whether prior distribution should be added to figure. Defaults to

`FALSE`

.- output_scale
transform the effect sizes and the meta-analytic effect size estimate to a different scale. Defaults to

`NULL`

which returns the same scale as the model was estimated on.- dots_prior
list of additional graphical arguments to be passed to the plotting function of the prior distribution. Supported arguments are

`lwd`

,`lty`

,`col`

, and`col.fill`

, to adjust the line thickness, line type, line color, and fill color of the prior distribution respectively.- ...
list of additional graphical arguments to be passed to the plotting function. Supported arguments are

`lwd`

,`lty`

,`col`

,`col.fill`

,`xlab`

,`ylab`

,`main`

,`xlim`

,`ylim`

to adjust the line thickness, line type, line color, fill color, x-label, y-label, title, x-axis range, and y-axis range respectively.

`plot.RoBMA`

returns either `NULL`

if `plot_type = "base"`

or an object object of class 'ggplot2' if `plot_type = "ggplot2"`

.