xpose.xtras (version 0.1.2)

roc_plot: ROC Plot for categorical DVs

Description

ROC Plot for categorical DVs

Usage

roc_plot(
  xpdb,
  mapping = NULL,
  cutpoint = 1,
  group = "ID",
  type = "ca",
  title = "ROC curve @dvcol~@probcol | @run",
  subtitle = "Ofv: @ofv, Eps shrink: @epsshk",
  caption = "@dir",
  tag = NULL,
  guide = TRUE,
  facets,
  .problem,
  quiet,
  ...
)

Value

A desired plot

Arguments

xpdb

<xp_xtras> or <xpose_data> object

mapping

ggplot2 style mapping

cutpoint

<numeric> Of defined probabilities, which one to use in plots.

group

Variable by which to group points or text

type

See Details.

title

Plot title

subtitle

Plot subtitle

caption

Plot caption

tag

Plot tag

guide

Include unity line?

facets

Additional facets

.problem

Problem number

quiet

Silence extra debugging output

...

Any additional aesthetics.

Details

For type-based customization of plots:

• c ROC curve (using geom_path)

• k Key points on ROC curve (where on curve the threshold is thres_fixed) (using geom_point)

• p ROC space points (using geom_point)

• t ROC space text (using geom_text)

• a AUC in bottom right (using geom_label)

See Also

catdv_vs_dvprobs()

Examples

# Note these examples are similar to catdv_vs_dvprobs

if (FALSE) {
# Test M3 model
pkpd_m3 %>%
  # Need to ensure var types are set
  set_var_types(catdv=BLQ,dvprobs=LIKE) %>%
  # Set probs
  set_dv_probs(1, 1~LIKE, .dv_var = BLQ) %>%
  # Optional, but useful to set levels
  set_var_levels(1, BLQ = lvl_bin()) %>%
  # Generate typical ROC curve
  roc_plot()

# Test categorical model
vismo_xpdb <- vismo_pomod  %>%
  set_var_types(.problem=1, catdv=DV, dvprobs=matches("^P\\d+$")) %>%
  set_dv_probs(.problem=1, 0~P0,1~P1,ge(2)~P23)

# Various cutpoints (note axes labels and texts)
vismo_xpdb %>%
  roc_plot(type = "p") # space plot
vismo_xpdb %>%
  roc_plot(cutpoint=2, type = "cak") # with area and key point
vismo_xpdb %>%
  roc_plot(cutpoint=3, type = "cak")

# alternative model example
vismo_xpdb2  <- vismo_dtmm   %>%
  set_var_types(.problem=1, catdv=DV, dvprobs=matches("^P\\d+$")) %>%
  set_dv_probs(.problem=1, 0~P0,1~P1,ge(2)~P23)
vismo_xpdb2 %>%
  roc_plot(cutpoint=2, type = "cak")
}