.rcspline.plot {CalibrationCurves}  R Documentation 
Internal function
Description
Adjusted version of the rcspline.plot
function where only the output is returned and no plot is made
Usage
.rcspline.plot(
x,
y,
model = c("logistic", "cox", "ols"),
xrange,
event,
nk = 5,
knots = NULL,
show = c("xbeta", "prob"),
adj = NULL,
xlab,
ylab,
ylim,
plim = c(0, 1),
plotcl = TRUE,
showknots = TRUE,
add = FALSE,
plot = TRUE,
subset,
lty = 1,
noprint = FALSE,
m,
smooth = FALSE,
bass = 1,
main = "auto",
statloc
)
Arguments
x 
a numeric predictor 
y 
a numeric response. For binary logistic regression, 
model 

xrange 
range for evaluating 
event 
event/censoring indicator if 
nk 
number of knots 
knots 
knot locations, default based on quantiles of 
show 

adj 
optional matrix of adjustment variables 
xlab 

ylab 

ylim 

plim 

plotcl 
plot confidence limits 
showknots 
show knot locations with arrows 
add 
add this plot to an already existing plot 
plot 
logical to indicate whether a plot has to be made. 
subset 
subset of observations to process, e.g. 
lty 
line type for plotting estimated spline function 
noprint 
suppress printing regression coefficients and standard errors 
m 
for 
smooth 
plot nonparametric estimate if 
bass 
smoothing parameter (see 
main 
main title, default is 
statloc 
location of summary statistics. Default positioning by clicking left mouse button where upper left corner of statistics should appear.
Alternative is 
Value
list with components (‘knots’, ‘x’, ‘xbeta’, ‘lower’, ‘upper’) which are respectively the knot locations, design matrix, linear predictor, and lower and upper confidence limits
See Also
lrm
, cph
, rcspline.eval
, plot
, supsmu
,
coxph.fit
, lrm.fit