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, ...)
data frame to plot
character name for x-axis data
character name for y-axis data
used to form y-axis label
used to form x-axis label
see defy()
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
if TRUE
, x- and y-axes will be log-transformed
if TRUE
, then the x- and y- axes will be forced
to have the same limits
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()
dv_pred
and dv_ipred
return a single plot; dv_preds
returns a list
of plots.
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.
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'
#>