Hmisc: rcspline.plot – R documentation

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rcspline.plot

Plot Restricted Cubic Spline Function

Description

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.

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,
              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, `y` should be either 0 or 1.
`model`	`"logistic"` or `"cox"`. For `"cox"`, uses the `coxph.fit` function with `method="efron"` arguement set.
`xrange`	range for evaluating `x`, default is `f` and 1 - \var{f} quantiles of `x`, where \var{f} = 10/max(\var{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 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
`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.

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

Author(s)

Frank Harrell
Department of Biostatistics, Vanderbilt University
fh@fharrell.com

Examples

#rcspline.plot(cad.dur, tvdlm, m=150)
#rcspline.plot(log10(cad.dur+1), tvdlm, m=150)

Hmisc

Harrell Miscellaneous

v4.5-0

GPL (>= 2)

Authors

Frank E Harrell Jr <fh@fharrell.com>, with contributions from Charles Dupont and many others.

Initial release

2021-02-27