Multiple `visreg`

objects can be bundled together in an object of class `visregList`

; for example, when you submit `visreg(fit)`

, you get a `visregList`

, one `visreg`

object for each predictor in the model. `visregList`

s can also be used for handling models with multiple outcomes.

For example, suppose we fit a multinomial regression model using the `nnet`

package:

```
library(nnet)
airquality$Heat <- cut(airquality$Temp,3,labels=c("Cool","Mild","Hot"))
fit <- multinom(Heat ~ Wind + Ozone, airquality)
```

By default, `visreg(fit, "Ozone")`

would create three separate plots, one for each level of the outcome, `Heat`

. By specifying `collapse=TRUE`

, we collapse the list down to a single `visreg`

object which can be plotted using the methods described here. For example:

```
visreg(fit, "Ozone", collapse=TRUE, overlay=TRUE, ylab="Probability",
ylim=c(0,1), partial=FALSE, rug=2)
```

Another example is quantile regression using the `quantreg`

package. Here, there is only one outcome, but we could be interested in modeling several different quantiles. The `collapse`

option is used similarly here:

```
library(quantreg)
fit <- rq(Ozone ~ Wind + Temp, tau=c(.25, .5, .75), data=airquality)
v <- visreg(fit, "Wind", overlay=TRUE, collapse=TRUE)
```

NOTE: `quantreg`

does not return standand errors if you specify multiple quantiles of interest. To obtain them, you must construct the `visregList`

manually:

```
fit1 <- rq(Ozone ~ Wind + Temp, tau=.25, data=airquality)
fit2 <- rq(Ozone ~ Wind + Temp, tau=.5, data=airquality)
fit3 <- rq(Ozone ~ Wind + Temp, tau=.75, data=airquality)
v <- visregList(visreg(fit1, "Wind", plot=FALSE),
visreg(fit2, "Wind", plot=FALSE),
visreg(fit3, "Wind", plot=FALSE),
labels=c("25%", "50%", "75%"), collapse=TRUE)
plot(v, ylab="Ozone", gg=TRUE)
# Loading required namespace: ggplot2
```

Notice the use of the `labels`

argument to label the elements of the list.