predict.HR | R Documentation |
predict method for an object of class 'HR'.
## S3 method for class 'HR' predict(object, predictor, prob=NULL, pred.value=NULL, conf.level=0.95, prediction.values=NULL, round.x=NULL, ref.label=NULL, ...)
object |
An object of class HR. |
predictor |
Variable named in the formula or included as a predictor in the |
prob |
Value between 0 and 1. If |
pred.value |
Value from the variable |
conf.level |
Level of confidence. Defaults to 0.95 (corresponding to 95%). |
prediction.values |
Vector of values ranging between minimum and maximum of the variable |
round.x |
Rounding of numbers in the predict. |
ref.label |
Label for the reference covariate. By default is the name of the covariate. |
... |
Other arguments. |
Returns a matrix with the prediction values.
Artur Araújo and Luís Meira-Machado
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, 11 pages. doi: 10.1155/2013/745742
smoothHR
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# 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) predict(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) ) pdval <- c(1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 15, 18, 22, 25) predict(hr2, predictor="los", pred.value=7, conf.level=0.95, prediction.values=pdval, ref.label="Ref.")
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