Plot DV versus predicted values

dv_pred(
  df,
  x = pm_axis_pred(),
  y = pm_axis_dv(),
  yname = "value",
  xname = "value",
  xs = list(),
  ys = list(),
  loglog = FALSE,
  scales = c("fixed", "free"),
  ...
)

dv_ipred(df, x = pm_axis_ipred(), ...)

dv_preds(df, ...)

Arguments

df	data frame to plot
x	character name for x-axis data
y	character name for y-axis data
yname	used to form y-axis label
xname	used to form x-axis label
xs	see `defx`
ys	see `defy`
loglog	if `TRUE`, x- and y-axes will be log-transformed
scales	if `TRUE`, then the x- and y- axes will be forced to have the same limits
...	passed to `scatt` and `layer_as`

Value

A single plot.

Details

Since this function creates a scatter plot, both the x and y columns must be numeric.

dv_preds returns a list of two plots, with the result of dv_pred in the first position and the result of dv_ipred in the second position. In this case, ... are passed to both functions.

Examples

df <- pmplots_data_obs()

dv_pred(df)
#> `geom_smooth()` using formula 'y ~ x'

dv_ipred(df, yname="MyDrug (ng/mL)")
#> `geom_smooth()` using formula 'y ~ x'
#> `geom_smooth()` using formula 'y ~ x'

dv_preds(df, yname = "MyDrug (ng/mL)")
#> [[1]]
#> `geom_smooth()` using formula 'y ~ x'
#> 
#> [[2]]
#> `geom_smooth()` using formula 'y ~ x'
#> `geom_smooth()` using formula 'y ~ x'
#>