| rcspline.plot {Hmisc} | R Documentation |
Provides plots of the estimated restricted cubic spline function relating
a single predictor to the response for a logistic or Cox model.
The rcspline.plot function does not allow for interactions as do
lrm and cph, but it can provide detailed output for
checking spline fits. This function uses the rcspline.eval,
lrm.fit, and Therneau's coxph.fit functions
and plots the estimated spline regression and confidence limits,
placing summary statistics on the graph. If there are no
adjustment variables, rcspline.plot can also plot two alternative
estimates of the regression function when model="logistic":
proportions or logit
proportions on grouped data, and a nonparametric estimate. The
nonparametric regression estimate is based on smoothing the binary
responses and taking the logit transformation of the smoothed
estimates, if desired. The smoothing uses supsmu.
rcspline.plot(x,y,model="logistic",xrange,event,nk=5,knots=NULL,
show="xbeta",adj=NULL,xlab,ylab,ylim,plim=c(0,1),plotcl=TRUE,
showknots=TRUE,add=FALSE,subset,lty=1,noprint=FALSE,m,smooth=FALSE,bass=1,
main="auto",statloc)
x |
a numeric predictor |
y |
a numeric response. For binary logistic regression, y should be 0-1.
|
model |
"logistic" or "cox". For "cox", uses the coxph.fit with
method="efron".
function.
|
xrange |
range for evaluating x, default is f and 1-f quantiles of x,
where f=10/max(n,200)
|
event |
event/censoring indicator if model="cox". If event is
present, model is assumed to be "cox"
|
nk |
number of knots |
knots |
knot locations, default based on quantiles of x (by
rcspline.eval)
|
show |
"xbeta" or "prob" - what is plotted on y-axis
|
adj |
optional matrix of adjustment variables |
xlab |
x-axis label, default is "label" attribute of x
|
ylab |
same for y |
ylim |
y-axis limits for logit or log hazard
|
plim |
y-axis limits for probability scale
|
plotcl |
plot confidence limits |
showknots |
show knot locations with arrows |
add |
add this plot to an already existing plot |
subset |
subset of observations to process, e.g. subset=sex=="male"
|
lty |
line type for plotting estimated spline function |
noprint |
suppress printing regression coefficients and standard errors |
m |
for model="logistic", plot grouped estimates with triangles. Each
group contains m ordered observations on x.
|
smooth |
plot nonparametric estimate if model="logistic" and adj is
not specified
|
bass |
smoothing parameter (see supsmu)
|
main |
main title, default is e.g. "Estimated Spline Transformation"
|
statloc |
location of summary statistics. Default positioning by
clicking left mouse button where upper left corner of statistics
should appear. Alternative is "ll" to place below the graph on the
lower left, or the actual x and y coordinates.
Use "none" to suppress statistics.
|
list with components knots, x, xbeta, lower, upper which are respectively
the knot locations, design matrix, linear predictor, and lower and upper
confidence limits
Frank Harrell
Department of Biostatistics, Vanderbilt University
f.harrell@vanderbilt.edu
lrm, cph, rcspline.eval, plot, supsmu, coxph.fit, lrm.fit
# rcspline.plot(cad.dur, tvdlm, m=150) # rcspline.plot(log10(cad.dur+1), tvdlm, m=150)