# rcspline.plot: Plot Restricted Cubic Spline Function In Hmisc: Harrell Miscellaneous

 rcspline.plot R Documentation

## 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,
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

`lrm`, `cph`, `rcspline.eval`, `plot`, `supsmu`, `coxph.fit`, `lrm.fit`
```#rcspline.plot(cad.dur, tvdlm, m=150)