Plot DV versus predicted values

Plots for DV versus population or individual predicted values. dv_preds makes both plots and returns them as a list (more in details).

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

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
ys	see defy()
xs	see defx(); note that xs defaults to ys so (by default) the scale configuration will be identical; pass both xs and ys to have them independently configured
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
logbr	when using log scale, should the tick marks be at full-log intervals or half-log intervals? If you pass null, the default scales will be used (which might be identical to full). Use xs and ys to pass custom scales.
...	passed to scatt() and layer_as()

Value

dv_pred and dv_ipred return a single plot; dv_preds returns a list of plots.

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'
#>