ExProb: Function Generator For Exceedance Probabilities
In rms: Regression Modeling Strategies

ExProb

R Documentation

Function Generator For Exceedance Probabilities

Description

For an orm object generates a function for computing the estimates of the function Prob(Y>=y) given one or more values of the linear predictor using the reference (median) intercept. This function can optionally be evaluated at only a set of user-specified y values, otherwise a right-step function is returned. There is a plot method for plotting the step functions, and if more than one linear predictor was evaluated multiple step functions are drawn. ExProb is especially useful for nomogram.

Optionally a normal approximation for a confidence interval for exceedance probabilities will be computed using the delta method, if conf.int > 0 is specified to the function generated from calling ExProb. In that case, a "lims" attribute is included in the result computed by the derived cumulative probability function.

Usage

ExProb(object, ...)

## S3 method for class 'orm'
ExProb(object, codes = FALSE, ...)

## S3 method for class 'ExProb'
plot(x, ..., data=NULL,
                      xlim=NULL, xlab=x$yname, ylab=expression(Prob(Y>=y)),
                      col=par('col'), col.vert='gray85', pch=20,
                      pch.data=21, lwd=par('lwd'), lwd.data=lwd,
                      lty.data=2, key=TRUE)

Arguments

`object`	a fit object from `orm`
`codes`	if `TRUE`, `ExProb` use the integer codes `1,2,\ldots,k` for the `k`-level response instead of its original unique values
`...`	ignored for `ExProb`. Passed to `plot` for `plot.ExProb`
`data`	Specify `data` if you want to add stratified empirical probabilities to the graph. If `data` is a numeric vector, it is assumed that no groups are present. Otherwise `data` must be a list or data frame where the first variable is the grouping variable (corresponding to what made the linear predictor vary) and the second variable is the data vector for the `y` variable. The rows of data should be sorted to be in order of the linear predictor argument.
`x`	an object created by running the function created by `ExProb`
`xlim`	limits for x-axis; default is range of observed `y`
`xlab`	x-axis label
`ylab`	y-axis label
`col`	color for horizontal lines and points
`col.vert`	color for vertical discontinuities
`pch`	plotting symbol for predicted curves
`lwd`	line width for predicted curves
`pch.data`, `lwd.data`, `lty.data`	plotting parameters for data
`key`	set to `FALSE` to suppress key in plot if `data` is given

Value

ExProb returns an R function. Running the function returns an object of class "ExProb".

Author(s)

Frank Harrell and Shengxin Tu

Examples

set.seed(1)
x1 <- runif(200)
yvar <- x1 + runif(200)
f <- orm(yvar ~ x1)
d <- ExProb(f)
lp <- predict(f, newdata=data.frame(x1=c(.2,.8)))
w <- d(lp)
s1 <- abs(x1 - .2) < .1
s2 <- abs(x1 - .8) < .1
plot(w, data=data.frame(x1=c(rep(.2, sum(s1)), rep(.8, sum(s2))),
                        yvar=c(yvar[s1], yvar[s2])))

qu <- Quantile(f)
abline(h=c(.1,.5), col='gray80')
abline(v=qu(.5, lp), col='gray80')
abline(v=qu(.9, lp), col='green')

rms documentation built on Sept. 11, 2024, 7:51 p.m.