For use with non-proportional hazards models (`survextrap(...,nonprop=TRUE)`

). Intended as a quick check of a model fit, so there are
limited customisation options.
The underlying data can be extracted with `hazard_ratio`

.

## Usage

```
plot_hazard_ratio(
x,
newdata = NULL,
t = NULL,
tmax = NULL,
niter = NULL,
ci = TRUE,
xlab = "Time",
ylab = "Hazard ratio",
line_size = 1.5,
ci_alpha = 0.2
)
```

## Arguments

- x
A fitted model object as returned by

`survextrap`

- newdata
A data frame with two rows. The hazard ratio will be defined as hazard(second row) divided by hazard(first row). If the only covariate in the model is a factor with two levels, then

`newdata`

defaults to a data frame containing the levels of this factor, so that the hazard ratio for the second level versus the first level is computed. For any other models,`newdata`

must be supplied explicitly.- t
Vector of times at which to compute the estimates.

- tmax
Maximum time at which to compute the estimates. If

`t`

is supplied, then this is ignored. If`t`

is not supplied, then`t`

is set to a set of 100 equally spaced time points from 0 to`tmax`

. If both`tmax`

and`t`

are not supplied, then`tmax`

is set to the maximum follow up time in the data.- niter
Number of MCMC iterations to use to compute credible intervals. Set to a low value to make this function quicker, at the cost of some approximation error (which may not be important for plotting or model development).

- ci
If

`TRUE`

then credible intervals are drawn. Defaults to drawing the intervals if the plot shows the curve for only one covariate value.- xlab
X-axis label

- ylab
Y-axis label

- line_size
Passed to

`geom_line`

- ci_alpha
Transparency for the credible interval ribbons