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=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,
subset, lty=1, noprint=FALSE, m, smooth=FALSE, bass=1,
main="auto", statloc)a numeric predictor
a numeric response. For binary logistic regression, y should
be either 0 or 1.
"logistic" or "cox". For "cox", uses the
coxph.fit function with method="efron" arguement set.
range for evaluating x, default is f and
\(1 - \var{f}\) quantiles of x, where
\(\var{f} = \frac{10}{\max{(\var{n}, 200)}}\)
event/censoring indicator if model="cox". If event is
present, model is assumed to be "cox"
number of knots
knot locations, default based on quantiles of x (by
rcspline.eval)
"xbeta" or "prob" - what is plotted on y-axis
optional matrix of adjustment variables
x-axis label, default is the “label” attribute of
x
y-axis label, default is the “label” attribute of
y
y-axis limits for logit or log hazard
y-axis limits for probability scale
plot confidence limits
show knot locations with arrows
add this plot to an already existing plot
subset of observations to process, e.g. sex == "male"
line type for plotting estimated spline function
suppress printing regression coefficients and standard errors
for model="logistic", plot grouped estimates with
triangles. Each group contains m ordered observations on
x.
plot nonparametric estimate if model="logistic" and
adj is not specified
smoothing parameter (see supsmu)
main title, default is "Estimated Spline Transformation"
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
# NOT RUN {
#rcspline.plot(cad.dur, tvdlm, m=150)
#rcspline.plot(log10(cad.dur+1), tvdlm, m=150)
# }
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