CalibrationCurves (version 2.0.6)

.rcspline.plot: 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
)

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

Arguments

x

a numeric predictor

y

a numeric response. For binary logistic regression, y should be either 0 or 1.

model

"logistic" or "cox". For "cox", uses the coxph.fit function with method="efron" argument set.

xrange

range for evaluating x, default is \(f\) and \(1 - f\) quantiles of x, where \(f = \frac{10}{\max{(n, 200)}}\) and \(n\) the number of observations

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 the “label” attribute of x

ylab

y-axis label, default is the “label” attribute of 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

plot

logical to indicate whether a plot has to be made. FALSE suppresses the plot.

subset

subset of observations to process, e.g. 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 "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.

See Also

lrm, cph, rcspline.eval, plot, supsmu, coxph.fit, lrm.fit