Plot curves of selected values (e.g., PPV or NPV) as a function of prevalence.

Source: R/plot_curve.R

plot_curve draws curves of selected values (including PPV, NPV) as a function of the prevalence (prev) for given values of sensitivity sens (or miss rate mirt) and specificity spec (or false alarm rate fart).

plot_curve(
  prev = num$prev,
  sens = num$sens,
  mirt = NA,
  spec = num$spec,
  fart = NA,
  what = c("prev", "PPV", "NPV"),
  p_lbl = "def",
  p_lwd = 2,
  what_col = pal,
  uc = 0,
  show_points = TRUE,
  log_scale = FALSE,
  prev_range = c(0, 1),
  lbl_txt = txt,
  main = txt$scen_lbl,
  sub = "type",
  title_lbl = NULL,
  cex_lbl = 0.85,
  col_pal = pal,
  mar_notes = FALSE,
  ...
)

Arguments

prev

The condition's prevalence prev (i.e., the probability of condition being TRUE). If prev = NA, the curves in what are plotted without points (i.e., show_points = FALSE).

sens

The decision's sensitivity sens (i.e., the conditional probability of a positive decision provided that the condition is TRUE). sens is optional when its complement mirt is provided.

mirt

The decision's miss rate mirt (i.e., the conditional probability of a negative decision provided that the condition is TRUE). mirt is optional when its complement sens is provided.

spec

The decision's specificity spec (i.e., the conditional probability of a negative decision provided that the condition is FALSE). spec is optional when its complement fart is provided.

fart

The decision's false alarm rate fart (i.e., the conditional probability of a positive decision provided that the condition is FALSE). fart is optional when its complement spec is provided.

what

Vector of character codes that specify the selection of curves to be plotted. Currently available options are c("prev", "PPV", "NPV", "ppod", "acc") (shortcut: what = "all"). Default: what = c("prev", "PPV", "NPV").

p_lbl

Type of label for shown probability values, with the following options:

  1. "abb": show abbreviated probability names;

  2. "def": show abbreviated probability names and values (default);

  3. "nam": show only probability names (as specified in code);

  4. "num": show only numeric probability values;

  5. "namnum": show names and numeric probability values;

  6. "no": hide labels (same for p_lbl = NA or NULL).

p_lwd

Line widths of probability curves plotted. Default: p_lwd = 2.

what_col

Vector of colors corresponding to the elements specified in what. Default: what_col = pal.

uc

Uncertainty range, given as a percentage of the current prev, sens, and spec values (added in both directions). Default: uc = .00 (i.e., no uncertainty). Plausible ranges are 0 < uc < .25.

show_points

Boolean value for showing the point of intersection with the current prevalence prev in all selected curves. Default: show_points = TRUE.

log_scale

Boolean value for switching from a linear to a logarithmic x-axis. Default: log_scale = FALSE.

prev_range

Range (minimum and maximum) of prev values on x-axis (i.e., values in c(0, 1) range). Default: prev_range = c(0, 1).

lbl_txt

Labels and text elements. Default: lbl_txt = txt.

main

Text label for main plot title. Default: main = txt$scen_lbl.

sub

Text label for plot subtitle (on 2nd line). Default: sub = "type" shows information on current plot type.

title_lbl

Deprecated text label for current plot title. Replaced by main.

cex_lbl

Scaling factor for the size of text labels (e.g., on axes, legend, margin text). Default: cex_lbl = .85.

col_pal

Color palette (if what_col is unspecified). Default: col_pal = pal.

mar_notes

Boolean value for showing margin notes. Default: mar_notes = FALSE.

...

Other (graphical) parameters.

Details

If no prevalence value is provided (i.e., prev = NA), the desired probability curves are plotted without showing specific points (i.e., show_points = FALSE).

Note that a population size N is not needed for computing probability information prob. (An arbitrary value can be used when computing frequency information freq from current probabilities prob.)

plot_curve is a generalization of plot_PV (see legacy code) that allows plotting additional dependent values.

See also

comp_prob computes current probability information; prob contains current probability information; comp_freq computes current frequency information; freq contains current frequency information; num for basic numeric parameters; txt for current text settings; pal for current color settings.

Other visualization functions: plot.riskyr(), plot_area(), plot_bar(), plot_crisk(), plot_fnet(), plot_icons(), plot_mosaic(), plot_plane(), plot_prism(), plot_tab(), plot_tree()

Examples

# Basics:
plot_curve()  # default curve plot, same as:

# plot_curve(what = c("prev", "PPV", "NPV"), uc = 0, prev_range = c(0, 1))

# Showing no/multiple prev values/points and uncertainty ranges:
plot_curve(prev = NA)  # default curves without prev value (and point) shown
#> No prevalence value provided: Plotting curves without points.

plot_curve(show_points = FALSE, uc = .10)  # curves w/o points, 10% uncertainty range

plot_curve(prev = c(.10, .33, .75))  # 3 prev values, with numeric point labels
#> Multiple prevalence values provided: Using numeric values to label points.

plot_curve(prev = c(.10, .33, .75), p_lbl = "no", uc = .10) # 3 prev, no labels, 10% uc
#> Multiple prevalence values provided: Using numeric values to label points.


# Provide local parameters and select curves:
plot_curve(prev = .2, sens = .8, spec = .6, what = c("PPV", "NPV", "acc"), uc = .2)


# Selecting curves: what = ("prev", "PPV", "NPV", "ppod", "acc") = "all"
plot_curve(prev = .3, sens = .9, spec = .8, what = "all")  # all curves

# plot_curve(what = c("PPV", "NPV"))                  # PPV and NPV
plot_curve(what = c("prev", "PPV", "NPV", "acc"))     # prev, PPV, NPV, and acc

# plot_curve(what = c("prev", "PPV", "NPV", "ppod"))  # prev, PPV, NPV, and ppod

# Visualizing uncertainty (uc as percentage range):
plot_curve(prev = .2, sens = .9, spec = .8, what = "all",
           uc = .10)  # all with a 10% uncertainty range

# plot_curve(prev = .3, sens = .9, spec = .8, what = c("prev", "PPV", "NPV"),
#            uc = .05)  # prev, PPV and NPV with a 5% uncertainty range

# X-axis on linear vs. log scale:
plot_curve(prev = .01, sens = .9, spec = .8)                    # linear scale

plot_curve(prev = .01, sens = .9, spec = .8, log_scale = TRUE)  # log scale

# Several small prev values:
plot_curve(prev = c(.00001, .0001, .001, .01, .05),
           sens = .9, spec = .8, log_scale = TRUE)
#> Multiple prevalence values provided: Using numeric values to label points.


# Zooming in by setting prev_range (of prevalence values):
plot_curve(prev = c(.25, .33, .40), prev_range = c(.20, .50),
           what = "all", uc = .05)
#> Multiple prevalence values provided: Using numeric values to label points.


# Probability labels:
plot_curve(p_lbl = "abb", what = "all")     # abbreviated names

plot_curve(p_lbl = "nam", what = "all")     # names only

plot_curve(p_lbl = "num", what = "all")     # numeric values only

plot_curve(p_lbl = "namnum", what = "all")  # names and values


# Text and color settings:
plot_curve(main = "Tiny text labels", p_lbl = "namnum", cex_lbl = .60)

plot_curve(main = "Specific colors", what = "all",
           uc = .1, what_col = c("grey", "red3", "green3", "blue3", "gold"))

plot_curve(main = "Black-and-white print version",
           what = "all", col_pal = pal_bwp)