rma.exact.fast: Compute a confidence interval for the grand mean at a...
In haben-michael/rma-exact-pkg: Exact CIs for random effects meta-analyses

Description Usage Arguments Value See Also Examples

Compute a confidence interval for the grand mean at a user-specified level.

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rma.exact.fast(yi, vi, c0 = 1, level = 0.05, plot = TRUE,
  tau2.bounds = NULL, resolution = 100, Z = NULL, B = 3000,
  tau2.alpha = 0.995)

`yi`	a vector containing the primary study measurements
`vi`	a vector of the same length as yi containing the variances of the of the primary study measurements contained in yi
`c0`	a vector containing the mixing parameters for the test statistics; defaults to 1
`level`	the level of the confidence interval; defaults to .05
`plot`	indicator whether to plot the contour of the confidence region; defaults to TRUE
`tau2.bounds`	upper and lower bounds for the range of population variance values for constructing the confidence region; if NULL, value will be calculated from tau2.alpha
`resolution`	resolution of the population variance values for constructing the confidence region; defaults to 1e2
`Z`	a matrix of length(yi) rows with each row consisting of standard normal samples to be used in the monte carlo estimation of the null distribution of the test statistic; if NULL, B values will be sampled per row
`B`	the number of monte carlo replicates per primary study observation to be used; defaults to 300
`tau2.alpha`	the level of the exact CI with which to bounds on population variance when constructing the confidence region

a matrix with length(c0) rows and each row containing the lower and upper endpoints of the confidence interval for the given mixing parameter

rma.exact for computing entire confidence regions

set.seed(1)
K <- 4
c0 <- c(.5,1)
yi=rnorm(K)*sqrt(vi+tau2)+mu0
vi <- (seq(1, 5, length=K))^2
Z <- matrix(rnorm(K*5e3),nrow=K)
rma.exact.fast(yi,vi,resolution=5e2)