plot.HR: Flexible hazard ratio curves taking a specific covariate... In smoothHR: Smooth Hazard Ratio Curves Taking a Reference Value

Description

Plots flexible hazard ratio curves allowing non-linear relationships between continuous predictors and survival. To better understand the effects that each continuous covariate has on the outcome, results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. Confidence bands for these curves are also derived.

Usage

 1 2 3 ## S3 method for class 'HR' plot(x, predictor, prob=NULL, pred.value=NULL, conf.level=0.95, round.x=NULL, ref.label=NULL, col, main, xlab, ylab, lty, xlim, ylim, xx, ...)

Arguments

 x An object of class HR predictor Variable named in the formula or included as a predictor in the coxfit. Usually a continuous predictor of survival for which the results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. prob Value between 0 and 1. If prob=0 the reference value will be the minimum of the hazard ratio curve. If prob=1 the reference value will be the maximum of the hazard ratio curve. For values between 0 and 1 the reference value will be the corresponding quantile of the variable predictor. pred.value Value from the variable predictor to be taken as the reference value. conf.level Level of confidence. Defaults to 0.95 (corresponding to 95%). round.x Rounding of numbers in the plot. ref.label Label for the reference covariate. By default is the name of the covariate. col Vector of dimension 3 for the colors to plot. main These arguments to title have useful defaults here. xlab The range of x and y values with sensible defaults. ylab The range of x and y values with sensible defaults. lty Vector of dimension 2 for the line type. xlim The range of x and y values with sensible defaults. ylim The range of x and y values with sensible defaults. xx Vector of values (from the variable predictor) to be shown in the x axis. ... Other arguments.

Value

No value is returned.

References

Cadarso-Suarez, C. and Meira-Machado, L. and Kneib, T. and Gude, F. (2010). Flexible hazard ratio curves for continuous predictors in multi-state models: an application to breast cancer data. Statistical Modelling, 10(3), 291-314. doi: 10.1177/1471082X0801000303

Meira-Machado, L. and Cadarso-Suárez, C. and Gude, F. and Araújo, A. (2013). smoothHR: An R Package for Pointwise Nonparametric Estimation of Hazard Ratio Curves of Continuous Predictors, Computational and Mathematical Methods in Medicine, 2013, Article ID 745742, 11 pages. doi: 10.1155/2013/745742

Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 # Example 1 library(survival) data(whas500) fit <- coxph(Surv(lenfol, fstat)~age+hr+gender+diasbp+pspline(bmi)+pspline(los), data=whas500, x=TRUE) hr1 <- smoothHR(data=whas500, coxfit=fit) plot(hr1, predictor="bmi", prob=0, conf.level=0.95) # Example 2 hr2 <- smoothHR( data=whas500, time="lenfol", status="fstat", formula=~age+hr+gender+diasbp+ pspline(bmi)+pspline(los) ) plot(hr2, predictor="los", pred.value=7, conf.level=0.95, xlim=c(0,30), round.x=1, ref.label="Ref.", xaxt="n") xx <- c(0, 5, 10, 15, 20, 25, 30) axis(1, xx)

Example output  