- model
a binary regression model fitted with `glm`

.

- main
user-specified main title.

- xlab
x-axis label. Defaults to the name of the (first) numeric predictor.

- ylab
y-axis label. Defaults to the name of the response -
within either 'P(...)' or 'logit(...)', depending on the response
type.

- xlim
Range of the x-axis. Defaults to the range of the numeric
predictor.

- ylim
Range of the y-axis. Defaults to the unit interval on
probability scale or the fitted values range on the link scale,
depending on `type`

.

- pred_var
character string of length 1 giving the name of
the numeric predictor. Defaults to the first one found in the data
set.

- pred_range
`"data"`

, `"xlim"`

, or a numeric vector.
If `"data"`

, the numeric predictor corresponds to the observed values. If
`"xlim"`

, 100 values are taken from the `"xlim"`

range. A numeric vector will be interpreted as the values to be predicted.

- group_vars
optional character string of conditioning
variables. Defaults to all factors found in the data set, response
excluded. If `FALSE`

, no variables are used for conditioning.

- base_level
vector of length one. If the response is a vector,
this specifies the base ('no effect') value of the
response variable
(e.g., "Placebo", 0, FALSE, etc.) and defaults
to the first level for
factor responses, or 0 for numeric/binary variables. This controls
which observations will be plotted on the top or the bottom of the
display. If the response is a matrix with success and failure
column, this specifies the one to be interpreted as failure
(default: 2), either as an integer, or as a
string (`"success"`

or `"failure"`

). The proportions of
*successes* will be plotted as observed values.

- subset
an optional vector specifying a subset of the data
rows. The value is evaluated in the data environment, so expressions
can be used to select the data (see examples).

- type
either "response" or "link" to select the scale of the
fitted values. The y-axis will be adapted accordingly.

- conf_level
confidence level used for calculating
confidence bands.

- delta
logical; indicates whether the delta method should be
employed for calculating the limits of the confidence band or not
(see details).

- pch
character or numeric vector of symbols used for plotting
the (possibly conditioned) observed values, recycled as needed.

- cex
size of the plot symbols (in lines).

- jitter_factor
argument passed to `jitter`

used for the points representing the observed values.

- lwd
Line width for the fitted values.

- lty
Line type for the fitted values.

- point_size
size of points for the fitted values in char units (default: 0, so
no points are plotted).

- col_lines, col_bands
character vector specifying the colors of the fitted
lines and confidence bands,
by default chosen with `rainbow_hcl`

. The
confidence bands are using alpha blending with alpha = 0.2.

- legend
logical; if `TRUE`

(default), a legend is drawn.

- legend_pos
numeric vector of length 2, specifying x and y
coordinates of the legend, or a character string (e.g., `"topleft"`

,
`"center"`

etc.). Defaults to `"topleft"`

if the fitted curve's slope is
positive, and `"topright"`

else.

- legend_inset
numeric vector or length 2 specifying the inset
from the legend's x and y coordinates in npc units.

- legend_vgap
vertical space between the legend's line entries.

- labels
logical; if `TRUE`

, labels corresponding to the
factor levels are plotted next to the fitted lines.

- labels_pos
either `"right"`

or `"left"`

, determining on which side
of the fitted lines (start or end) the labels should be placed.

- labels_just
character vector of length 2, specifying the
relative justification of the labels to their coordinates. See the
documentation of the `just`

parameter of
`grid.text`

for more details.

- labels_offset
numeric vector of length 2, specifying the offset
of the labels' coordinates in npc units.

- gp_main
object of class `"gpar"`

used for the main title.

- gp_legend_frame
object of class `"gpar"`

used for the
legend frame.

- gp_legend_title
object of class `"gpar"`

used for the
legend title.

- newpage
logical; if `TRUE`

, the plot is drawn on a new page.

- pop
logical; if `TRUE`

, all newly generated viewports are
popped after plotting.

- return_grob
logical. Should a snapshot of the display be
returned as a grid grob?

- a
intercept; alternatively, a regression model from which
coefficients can be extracted via `coef`

.

- b
slope.

- ...
Further arguments passed to `grid.abline`

.