bootBCa: BCa Bootstrap on Existing Bootstrap Replicates

In rms: Regression Modeling Strategies

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)

rms documentation built on April 12, 2025, 1:18 a.m.