predictRisk.penCSC

predictRisk method for absolute risk prediction. This is mainly for compatibility of 'CSCNet' with functions of 'riskRegression' package.

Usage

# S3 method for penCSC
predictRisk(object, newdata, times, cause, ...)

Arguments

object: An object of class 'penCSC'.
newdata: A data frame containing the variable information of new records.
times: A vector of time horizons which we want the absolute risk predictions at.
cause: A single value indicating the event of interest which we want the absolute risk predictions for. This value should be one of the values in the status variable of the data.
...: Additional arguments. Not used by predictRisk.penCSC.

Value

A matrix with columns of absolute risk predictions of individuals for each requested time horizon.

References

Wickham H, Averick M, Bryan J, Chang W, McGowan L, François R, et al. Welcome to the tidyverse. J Open Source Softw. 2019 Nov 21;4(43):1686.

Bache S, Wickham H (2022). magrittr: A Forward-Pipe Operator for R. https://magrittr.tidyverse.org, https://github.com/tidyverse/magrittr.

Author

Shahin Roshani

Examples


library(riskRegression)

data(Melanoma)

vl <- list('1'=c('age','sex','ulcer','thick'),

          '2'=~age+sex+epicel+thick+ici)

al <- list('1'=0,'2'=.5)

ll <- list('1'=.01,'2'=.04)

penfit <- penCSC(time='time',status='status',vars.list=vl,

                data=Melanoma,alpha.list=al,lambda.list=ll)

predictRisk(penfit,Melanoma[1:5,],times=1825*(1:2),cause=1)
#>           1825      3650
#> [1,] 0.5989514 0.7634726
#> [2,] 0.1245976 0.2072521
#> [3,] 0.1147573 0.1931740
#> [4,] 0.1213908 0.1996565
#> [5,] 0.7199651 0.8683818