bcci: Bias-Corrected Confidence Intervals

In jeksterslabds/jeksterslabRmedsimple: Jekster's Lab Simple Mediation Model Utilities

Description

Bias-Corrected Confidence Intervals

Usage

bcci(thetahatstar, thetahat, theta = NULL, alpha = c(0.001, 0.01, 0.05))

Arguments

thetahatstar	Numeric vector. Sampling distribution of thetahat.
thetahat	Numeric. Parameter estimate.
theta	Numeric. Parameter. Optional argument.
alpha	Numeric vector. Alpha level. By default alpha = c(0.001, 0.01, 0.05).

Author(s)

Ivan Jacob Agaloos Pesigan

See Also

Other confidence intervals functions: bcaci(), evalci(), len(), pcci(), shape(), theta_hit(), zero_hit()

Examples

B <- 5000
data <- jeksterslabRdatarepo::thirst
thetahat <- fit.ols(data, minimal = TRUE)
n <- nrow(data)
muthetahat <- colMeans(data)
Sigmathetahat <- cov(data)
thetahatstar <- pb.mvn(
  muthetahat = muthetahat, Sigmathetahat = Sigmathetahat,
  n = n, B = 5000, par = FALSE
)
bcci(
  thetahatstar = thetahatstar,
  thetahat = thetahat,
  theta = 0.15 # assuming that the true indirect effect is 0.15
)

jeksterslabds/jeksterslabRmedsimple documentation built on Oct. 16, 2020, 11:30 a.m.