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

Value

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

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

Author

Frank Harrell and Shengxin Tu

Examples

Run this code

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')