plot_curve {riskyr} | R Documentation |
Plot curves of selected values (e.g., PPV or NPV) as a function of prevalence.
Description
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
).
Usage
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 |
sens |
The decision's sensitivity |
mirt |
The decision's miss rate |
spec |
The decision's specificity |
fart |
The decision's false alarm rate |
what |
Vector of character codes that specify the
selection of curves to be plotted. Currently available
options are |
p_lbl |
Type of label for shown probability values, with the following options:
|
p_lwd |
Line widths of probability curves plotted.
Default: |
what_col |
Vector of colors corresponding to the elements
specified in |
uc |
Uncertainty range, given as a percentage of the current
|
show_points |
Boolean value for showing the point of
intersection with the current prevalence |
log_scale |
Boolean value for switching from a linear
to a logarithmic x-axis.
Default: |
prev_range |
Range (minimum and maximum) of |
lbl_txt |
Labels and text elements.
Default: |
main |
Text label for main plot title.
Default: |
sub |
Text label for plot subtitle (on 2nd line).
Default: |
title_lbl |
Deprecated text label for current plot title.
Replaced by |
cex_lbl |
Scaling factor for the size of text labels
(e.g., on axes, legend, margin text).
Default: |
col_pal |
Color palette (if what_col is unspecified).
Default: |
mar_notes |
Boolean value for showing margin notes.
Default: |
... |
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
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
plot_curve(prev = c(.10, .33, .75), p_lbl = "no", uc = .10) # 3 prev, no labels, 10% uc
# 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)
# 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)
# 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)