crisk.pre.bart {BART} | R Documentation

## Data construction for competing risks with BART

### Description

Competing risks contained in (t, δ, x) must be translated to data suitable for the BART competing risks model; see `crisk.bart` for more details.

### Usage

    crisk.pre.bart( times, delta, x.train=NULL, x.test=NULL,
                    x.train2=x.train, x.test2=x.test, K=NULL )

### Arguments

`times` | The time of event or right-censoring.
`delta` | The event indicator: 1 is a cause 1 event, 2 a cause 2 while 0 is censored.
`x.train` | Explanatory variables for training (in sample) data of cause 1. If provided, must be a matrix with (as usual) rows corresponding to observations and columns to variables.
`x.test` | Explanatory variables for test (out of sample) data of cause 1. If provided, must be a matrix and have the same structure as x.train.
`x.train2` | Explanatory variables for training (in sample) data of cause 2. If provided, must be a matrix with (as usual) rows corresponding to observations and columns to variables.
`x.test2` | Explanatory variables for test (out of sample) data of cause 2. If provided, must be a matrix and have the same structure as x.train.
`K` | If provided, then coarsen `times` per the quantiles 1/K, 2/K, ..., K/K.

### Value

`surv.pre.bart` returns a list. Besides the items listed below, the list has a `times` component giving the unique times and `K` which is the number of unique times.

`y.train` | A vector of binary responses for cause 1.
`y.train2` | A vector of binary responses for cause 2.
`cond` | A vector of indices of `y.train` indicating censored subjects.
`binaryOffset` | The binary offset for `y.train`.
`binaryOffset2` | The binary offset for `y.train2`.
`tx.train` | A matrix with rows consisting of time and the covariates of the training data for cause 1.
`tx.train2` | A matrix with rows consisting of time and the covariates of the training data for cause 2.
`tx.test` | A matrix with rows consisting of time and the covariates of the test data, if any, for cause 1.
`tx.test2` | A matrix with rows consisting of time and the covariates of the test data, if any, for cause 2.

### Author(s)

Rodney Sparapani: rsparapa@mcw.edu

### References

Sparapani, R., Logan, B., McCulloch, R., and Laud, P. (2016) Nonparametric survival analysis using Bayesian Additive Regression Trees (BART). Statistics in Medicine, 16:2741-53 <doi:10.1002/sim.6893>.

### See Also

`crisk.bart`

### Examples

    data(transplant)

    delta <- (as.numeric(transplant$event)-1)

    delta[delta==1] <- 4
    delta[delta==2] <- 1
    delta[delta>1] <- 2
    table(delta, transplant$event)

    table(1+floor(transplant$futime/30.5)) ## months
    times <- 1+floor(transplant$futime/30.5)

    typeO <- 1*(transplant$abo=='O')
    typeA <- 1*(transplant$abo=='A')
    typeB <- 1*(transplant$abo=='B')
    typeAB <- 1*(transplant$abo=='AB')
    table(typeA, typeO)

    x.train <- cbind(typeO, typeA, typeB, typeAB)

    N <- nrow(x.train)

    x.test <- x.train

    x.test[1:N, 1:4] <- matrix(c(1, 0, 0, 0), nrow=N, ncol=4, byrow=TRUE)

    pre <- crisk.pre.bart(x.train=x.train, times=times, delta=delta, x.test=x.test)

[Package BART version 2.5 Index]