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"),
  what_col = pal, uc = 0, show_points = TRUE, log_scale = FALSE,
  lbl_txt = txt, title_lbl = NA, p_lbl = "def", cex_lbl = 0.85,
  col_pal = pal, mar_notes = TRUE, ...)

Arguments

prev

The condition's prevalence prev (i.e., the probability of condition being TRUE).

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").

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.

lbl_txt

Labels and text elements. Default: lbl_txt = txt.

title_lbl

Main plot title. Default: title_lbl = NA (using lbl_txt$scen_lbl).

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).

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 = TRUE.

...

Other (graphical) parameters.

Details

plot_curve is a generalization of plot_PV (see legacy code) that allows for 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_fnet, plot_icons, plot_mosaic, plot_plane, plot_prism, plot_tab, plot_tree

Examples

# Basics: # (1) Plot current freq and prob values: plot_curve() # default curve plot,
# same as: # plot_curve(what = c("prev", "PPV", "NPV")) # hide points and show uncertainty: plot_curve(show_points = FALSE, uc = .10) # default w/o points, 10% uncertainty range
# (2) Provide local parameters and select curves: plot_curve(prev = .2, sens = .8, spec = .6, what = c("PPV", "NPV", "acc"), uc = .2)
# All curves: what = ("prev", "PPV", "NPV", "ppod", "acc") plot_curve(prev = .3, sens = .9, spec = .8, what = "all", col_pal = pal_org) # all curves.
# Selected 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 = .3, sens = .9, spec = .8, what = c("prev", "PPV", "NPV"), uc = .05) # => prev, PPV and NPV with a 5% uncertainty range
plot_curve(prev = .2, sens = .8, spec = .7, what = "all", uc = .10) # => all with a 10% uncertainty range
# X-axis as 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
plot_curve(prev = .0001, sens = .7, spec = .6) # linear scale
plot_curve(prev = .0001, sens = .7, spec = .6, log_scale = TRUE) # log scale
# 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(title_lbl = "Testing tiny text labels", cex_lbl = .60)
plot_curve(title_lbl = "Testing specific colors", uc = .05, what = "all", what_col = c("grey", "red3", "green3", "blue3", "gold"))
plot_curve(title_lbl = "Testing color palette", uc = .05, what = "all", col_pal = pal_org)