A model fit by crr.fit

A character vector specifying the new labels for variables in a fit.

Other arguments for Newlabels

A model fit by crr.fit

A list of named vectors specifying the new level labels for categorical predictors.

Other arguments for Newlevels

A model fit by crr.fit

Not used

A risk score (typically a probability giving the risk of event failure)

The event status

The event times. Applies when the type argument is "survival" or "crr"

The outcome type: "logistic" for binary, "survival" for ordinary time-to-event, and "crr" for competing risks outcomes. Defaults to "crr".

The value of fstatus that indicates the event of interest. Defaults to 1.

The censoring event code. Defaults to 0.

Error tolerance (not used)

Total number of observations in the input data

Number of observations used for calculation

Total number of usable pairs

Number of concordant pairs

The concordance index: number of concordant pairs divided by the total number of usable pairs

A Cox proportional hazards regression model constructed from cph (by Frank Harrell)

The value of the status column that indicates a censored observation

The value of the status column that indicates the event of interest

the estimated regression coefficients

log pseudo-liklihood evaluated at coef

derivitives of the log pseudo-likelihood evaluated at coef

-second derivatives of the log pseudo-likelihood

estimated variance covariance matrix of coef

matrix of residuals giving the contribution to each score (columns) at each unique failure time (rows)

vector of unique failure times

jumps in the Breslow-type estimate of the underlying sub-distribution cumulative hazard (used by predict.crr())

the tfs matrix (output of tf(), if used)

TRUE if the iterative algorithm converged.

the value of the status indicator that indicates a censored observation

the value of the status indicator that indicates an event of interest

regular survival model fitted by cph which is saved for function nomogram.crr to adjust lp for competing risks

data used for cph model, where all predictors are represented in numeric format, which is used by function tenf.crr to do ten fold cross-validation

A numeric variable to assess calibration for

The event time variable. See cuminc.

The event status variable. See cuminc.

A single time point to assess calibration at

The censoring event code. See cuminc.

The value of fstatus that indicates the event of interest

Should the failure probability be assessed? Defaults to TRUE. If FALSE, the event-free probability is assessed.

Minimum number of observations in each group. See cut2.

Number of quantile groups. See cut2.

Actual cut points to use for x. See cut2.

Should the calibration curve be plotted? Defaults to TRUE.

Confidence limit on error bars. Defaults to 0.95. Set to FALSE to suppress.

The x-axis label. Uses label or name of calling argument if not specified.

The y-axis label. Uses a default label is none specified.

The x-axis limits. Defaults to c(0, 1).

The y-axis limits. Defaults to c(0, 1).

Line type for connecting estimates and error bars

Defaults to FALSE. Set to TRUE to add to an existing plot.

Character size for subtitle (default 0.7). Defaults to FALSE to suppress.

Should a reference line be added? See abline.

The intercept for the reference line. See abline.

The slope for the reference line. See abline.

Other arguments passed to lines and errbar.

Mean value of x

Number of observations

Number of events (of type failcode)

Estimated cumulative incidence (or event-free probability if ci=FALSE)

Estimated standard error for the ci value

A model fit by crr.fit

A vector of time points to display failure probability axes for.

Should the failure probability be displayed? Defaults to TRUE. If FALSE, the event-free probability is displayed.

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 the 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.

If datadist was not defined for all predictors, it is required to define adjustment settings for the undefined ones (e.g. adj.to=list(age=50, sex="female")).

Set to FALSE to suppress creation of an axis for scoring X\beta. Defaults to TRUE.

If lp=TRUE, specifies a vector of settings of X\beta. Default is to use pretty(range of linear predictors, nint).

label for linear predictor axis. Default is "Linear Predictor".

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).

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.

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.

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).

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")).

For models such as the ordinal logistic model with multiple intercepts, specifies which one to use in evaluating the linear predictor.

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.

Colors corresponding to conf.int. Use fractions for gray scale (for UNIX S-PLUS).

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.

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.

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.

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.

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.

Default maximum point score is 100.

Number of intervals to label for axes representing continuous variables. See pretty.

Specify label.every=i to label on every ith tick mark.

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)

Fraction of horizontal plot to set aside for axis titles

Character size for tick mark labels

Character size for axis titles (variable names)

If col.grid=1, no gray scale is used, but an ordinary line is drawn. If 0<col.grid<1, a col (gray scale) of col.grid is used to draw vertical reference lines for major axis divisions and col.grid/2 for minor divisions. The default is col.grid=FALSE, i.e., reference lines are omitted. Specifying col.grid=TRUE is the same as specifying a gray scale level of col.grid=.2 (5 for Windows S-PLUS).

By default, variable labels are used to label axes. Set vnames="names" to instead use variable names.

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)".

If varname.label=TRUE, you can change the separator to something other than = by specifying this parameter.

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.

See tck under par.

Spacing between numeric axis labels and axis (see par for mgp)

Vector of character strings containing names of variables for which to suppress drawing axes. Default is to show all variables.

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.

A character string giving the axis label for the points scale

A character string giving the axis label for the total points scale

Set to TRUE to force the total points and later axes to be placed on a separate page

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))).

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.

Setting the minimal value in the total point axis on the nomogram.

Setting the maximal value in the total point axis.

The predictor variables specified by their names here will not be shown in the nomogram. The predicted outcome based on this reduced nomogram would be the same as if users were using the full version of the nomogram by entering the some values for the predictors remaining in the reduced nomogram but adjusted values for the hiden predictors so that 0 points will be achieved from these hiden predictor variables in the full nomogram.

A regression model that was created with library(rms) in effect, 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.

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").

Set to FALSE to suppress creation of an axis for scoring X\beta.

If lp=TRUE, lp.at may specify a vector of settings of X\beta. Default is to use pretty(range of linear predictors, nint).

label for linear predictor axis. Default is "Linear Predictor".

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.

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).

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.

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.

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).

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")).

for models such as the ordinal logistic model with multiple intercepts, specifies which one to use in evaluating the linear predictor.

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.

colors corresponding to conf.int. Use fractions for gray scale(for UNIX S-PLUS).

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

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.

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

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.

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

default maximum point score is 100

number of intervals to label for axes representing continuous variables. See pretty.

Specify label.every = i to label on every ith tick mark

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)

fraction of horizontal plot to set aside for axis titles

character size for tick mark labels

character size for axis titles (variable names)

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)).

By default, variable labels are used to label axes. Set vnames = "names" to instead use variable names.

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)".

If varname.label = TRUE, you can change the separator to something other than = by specifying this parameter.

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.

see tck under par

length of tick marks in nomogram

spacing between numeric axis labels and axis (see par for mgp)

vector of character strings containing names of variables for which to suppress drawing axes. Default is to show all variables.

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.

a character string giving the axis label for the points scale

a character string giving the axis label for the total points scale

set to TRUE to force the total points and later axes to be placed on a separate page

a user-provided function that will be executed before the total points axis is drawn. Default is not toe xecute 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))).

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.

logical: should the factor labels have their first letter capitalized?

the minimum point for the total point axis

the maxmum point for the total point axis

specified survival time for the predicted survival probability

a modified version of omit

A cuminc object

A single time point to return the cumulative incidence at

The value of the status column that indicates the event of interest

The group name. If the group argument was used in the cuminc fit, there will be one row per group. Otherwise this is non-informative.

The cumulative incidence probability at the desired time point

The estimated variance of the cumulative incidence estimate

A model fit by crr.fit

A data.frame for prediction containing values of covariates in the model. If missing, the model development dataset (object$cphdat) is used.

A single time point to calculate the failure probability

Should the linear predictor be returned instead of the failure probability? Defaults to FALSE.

Additional arguments such as cov2 as in crr

A model fit by crr.fit

A single time point to calculate the failure probability

Should we only display the failure probability at the specified time? Defaults to FALSE.

An optional connection or character string naming the file to print to.

Only used if the file argument is specified. If TRUE, the output will be appended to file, otherwise it will overwritten.

A model fit by crr.fit

Other arguments for summary.rms

A model fit by crr.fit

A single time point to calculate the failure probability

Should the linear predictor be returned instead of the failure probability? Defaults to FALSE.

The number of folds. Defaults to 10.

Should the progress of cross-validation be printed to the console? Defaults to TRUE.