- fit
a regression model fit that was created with rms, and
(usually) with options(datadist = "object.name") in effect.
- ...
settings of variables to use in constructing axes. If datadist
was in effect, the default is to use pretty(total range, nint)
for continuous variables, and the class levels for discrete ones.
For legend.nomabbrev, ... specifies optional
parameters to pass
to legend. Common ones are bty = "n" to suppress drawing the
box. You may want to specify a non-proportionally spaced font
(e.g., courier) number if abbreviations are more than one letter long.
This will make the abbreviation definitions line up (e.g., specify
font = 2, the default for courier). Ignored for print
and plot.
- adj.to
If you didn't define datadist for all predictors, you will have to
define adjustment settings for the undefined ones, e.g.
adj.to= list(age = 50, sex = "female").
- lp
Set to FALSE to suppress creation of an axis for scoring
\(X\beta\).
- lp.at
If lp=TRUE, lp.at may specify a vector of settings of
\(X\beta\).
Default is to use pretty(range of linear predictors, nint).
- fun
an optional function to transform the linear predictors, and to plot
on another axis. If more than one transformation is plotted, put
them in a list, e.g. list(function(x) x/2, function(x) 2*x).
Any function values equal to NA will be ignored.
- fun.at
function values to label on axis. Default fun evaluated
at lp.at. If more than one fun was specified, using a vector
for fun.at will cause all functions to be evaluated at the same
argument values. To use different values, specify a list of vectors for
fun.at, with elements corresponding to the different functions
(lists of vectors also applies to fun.lp.at and fun.side).
- fun.lp.at
If you want to
evaluate one of the functions at a different set of linear predictor
values than may have been used in constructing the linear predictor axis,
specify a vector or list of vectors
of linear predictor values at which to evaluate the function. This is
especially useful for discrete functions. The presence of this attribute
also does away with the need for nomogram to compute numerical approximations of
the inverse of the function. It also allows the user-supplied function
to return factor objects, which is useful when e.g. a single tick
mark position actually represents a range.
If the fun.lp.at parameter is present, the fun.at
vector for that function is ignored.
- funlabel
label for fun axis. If more than one function was given but
funlabel is of length one, it will be duplicated as needed. If fun is
a list of functions for which you specified names (see the final example
below), these names will be used as labels.
- interact
When a continuous variable interacts with a discrete one, axes are
constructed so that the continuous variable moves within the axis, and
separate axes represent levels of interacting factors. For interactions
between two continuous variables, all but the axis variable must have
discrete levels defined in interact.
For discrete interacting factors, you may specify levels to use in
constructing the multiple axes. For continuous interacting factors,
you must do this. Examples: interact = list(age = seq(10,70,by=10),
treat = c("A","B","D")).
- kint
for models such as the ordinal models with multiple intercepts,
specifies which one to use in evaluating the linear predictor.
Default is to use fit$interceptRef if it exists, or 1.
- conf.int
confidence levels to display for each scoring. Default is FALSE to display
no confidence limits. Setting conf.int to TRUE is the same as
setting it to c(0.7, 0.9),
with the line segment between the 0.7 and 0.9 levels shaded using
gray scale.
- conf.lp
default is "representative" to group all linear predictors evaluated
into deciles, and to show, for the linear predictor confidence intervals,
only the mean linear predictor within the deciles along with the median
standard error within the deciles. Set conf.lp = "none" to suppress
confidence limits for the linear predictors, and to "all" to show
all confidence limits.
- est.all
To plot axes for only the subset of variables named in ..., set
est.all = FALSE. Note: This option only works when zero has a special
meaning for the variables that are omitted from the graph.
- posterior.summary
when operating on a Bayesian model such as a
result of blrm specifies whether to use posterior mean
(default) vs. posterior mode/median of parameter values in constructing
the nomogram
- abbrev
Set to TRUE to use the abbreviate function to abbreviate levels of
categorical factors, both for labeling tick marks and for axis titles.
If you only want to abbreviate certain predictor variables, set abbrev
to a vector of character strings containing their names.
- minlength
applies if abbrev = TRUE. Is the minimum abbreviation length passed to the
abbreviate function. If you set minlength = 1, the letters of the
alphabet are used to label tick marks for categorical predictors, and
all letters are drawn no matter how close together they are. For
labeling axes (interaction settings), minlength = 1 causes
minlength = 4 to be used.
- maxscale
default maximum point score is 100
- nint
number of intervals to label for axes representing continuous variables.
See pretty.
- vnames
By default, variable labels are used to label axes. Set
vnames = "names"
to instead use variable names.
- omit
vector of character strings containing names of variables for which to
suppress drawing axes. Default is to show all variables.
- verbose
set to TRUE to get printed output detailing how tick marks are chosen
and labeled for function axes. This is useful in seeing how certain
linear predictor values cannot be solved for using inverse linear
interpolation on the (requested linear predictor values, function values at
these lp values). When this happens you will see NAs in the verbose
output, and the corresponding tick marks will not appear in the nomogram.
- x
an object created by nomogram, or the x coordinate for
a legend
- dec
number of digits to the right of the decimal point, for rounding
point scores in print.nomogram. Default is to round to the nearest
whole number of points.
- lplabel
label for linear predictor axis. Default is "Linear Predictor".
- fun.side
a vector or list of vectors of side parameters for the axis function
for labeling function values.
Values may be 1 to position a tick mark label below the axis (the default),
or 3 for above the axis. If for example an axis has 5 tick mark labels
and the second and third will run into each other, specify
fun.side=c(1,1,3,1,1) (assuming only one function is specified as fun).
- col.conf
colors corresponding to conf.int.
- conf.space
a 2-element vector with the vertical range within which to draw
confidence bars, in units of 1=spacing between main bars. Four heights
are used within this range (8 for the linear predictor if more than
16 unique values were evaluated), cycling them among separate confidence
intervals to reduce overlapping.
- label.every
Specify label.every = i to label on every ith tick mark.
- force.label
set to TRUE to force every tick mark intended to be labeled to have
a label plotted (whether the labels run into each other or not)
- xfrac
fraction of horizontal plot to set aside for axis titles
- cex.axis
character size for tick mark labels
- cex.var
character size for axis titles (variable names)
- col.grid
If left unspecified, no vertical reference lines are drawn. Specify a
vector of length one (to use the same color for both minor and major
reference lines) or two (corresponding to the color for the major and
minor divisions, respectively) containing colors, to cause vertical reference
lines to the top points scale to be drawn. For R, a good choice is
col.grid = gray(c(0.8, 0.95)).
- varname.label
In constructing axis titles for interactions, the default is to add
(interacting.varname = level) on the right. Specify
varname.label = FALSE
to instead use "(level)".
- varname.label.sep
If varname.label = TRUE, you can change the separator to something other than
= by specifying this parameter.
- ia.space
When multiple axes are draw for levels of interacting factors, the
default is to group combinations related to a main effect. This is
done by spacing the axes for the second to last of these
within a group only
0.7 (by default) of the way down as compared with normal space of 1 unit.
- tck
see tck under par
- tcl
length of tick marks in nomogram
- lmgp
spacing between numeric axis labels and axis (see par
for mgp)
- naxes
maximum number of axes to allow on one plot. If the nomogram requires more
than one “page”, the “Points” axis will be repeated at
the top of each page when necessary.
- points.label
a character string giving the axis label for the points scale
- total.points.label
a character string giving the axis label for the total points scale
- total.sep.page
set to TRUE to force the total points and later axes to be placed on a
separate page
- total.fun
a user-provided function that will be executed before the total points
axis is drawn. Default is not to execute a function. This is useful e.g.
when total.sep.page = TRUE and you wish to use locator to find the
coordinates for positioning an abbreviation legend before it's too late
and a new page is started (i.e., total.fun = function() print(locator(1))).
- cap.labels
logical: should the factor labels have their first
letter capitalized?
- object
the result returned from nomogram
- which
a character string giving the name of a variable for which to draw a
legend with abbreviations of factor levels
- y
y-coordinate to pass to the legend function. This is the upper left
corner of the legend box. You can omit y if x is a list with
named elements x and y. To use the mouse to locate the legend,
specify locator(1) for x. For print, x is
the result of nomogram.
- ncol
the number of columns to form in drawing the legend.