R: BCa Bootstrap on Existing Bootstrap Replicates

bootBCa {rms} | R Documentation

## BCa Bootstrap on Existing Bootstrap Replicates

### Description

This functions constructs an object resembling one produced by the `boot` package's `boot` function, and runs that package's `boot.ci` function to compute BCa and percentile confidence limits. `bootBCa` can provide separate confidence limits for a vector of statistics when `estimate` has length greater than 1. In that case, `estimates` must have the same number of columns as `estimate` has values.

### Usage

    bootBCa(estimate, estimates, type=c('percentile','bca','basic'),
                   n, seed, conf.int = 0.95)

### Arguments

`estimate` | original whole-sample estimate
`estimates` | vector of bootstrap estimates
`type` | type of confidence interval, defaulting to nonparametric percentile
`n` | original number of observations
`seed` | `.Random.seem` in effect before bootstrap estimates were run
`conf.int` | confidence level

### Value

a 2-vector if `estimate` is of length 1, otherwise a matrix with 2 rows and number of columns equal to the length of `estimate`

### Note

You can use `if(!exists('.Random.seed')) runif(1)` before running your bootstrap to make sure that `.Random.seed` will be available to `bootBCa`.

### Author(s)

Frank Harrell

### See Also

`boot.ci`

### Examples

    ## Not run:
    x1 <- runif(100); x2 <- runif(100); y <- sample(0:1, 100, TRUE)
    f <- lrm(y ~ x1 + x2, x=TRUE, y=TRUE)
    seed <- .Random.seed
    b <- bootcov(f)
    # Get estimated log odds at x1=.4, x2=.6
    X <- cbind(c(1,1), x1=c(.4,2), x2=c(.6,3))
    est <- X
    ests <- t(X
    bootBCa(est, ests, n=100, seed=seed)
    bootBCa(est, ests, type='bca', n=100, seed=seed)
    bootBCa(est, ests, type='basic', n=100, seed=seed)

    ## End(Not run)

[Package rms version 5.1-1 Index]