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.
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
Returns
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
Author(s)
Frank Harrell
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.
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=.6X <- 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)