# rma.exact.fast: Compute a confidence interval for the grand mean at a... In rma.exact: Exact Confidence Intervals for Random Effects Meta-Analyses

## Description

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

## Usage

 ```1 2 3 4``` ```rma.exact.fast(yi, vi, c0 = 1.2 * (length(yi) < 6) + 0.6 * (length(yi) >= 6 & length(yi) < 10) + 0.2 * (length(yi) >= 10), level = 0.05, plot = TRUE, tau2.bounds = NULL, resolution = 100, Z = NULL, B = 3000, tau2.alpha = 0.995) ```

## Arguments

 `yi` vector of measurements from the primary studies `vi` vector of the variances of the measurements in yi `c0` vector of the mixing parameters for the test statistics `level` the level of the confidence interval `plot` indicator whether to plot the contour of the confidence region `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 `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 `tau2.alpha` the level of the exact CI with which to bounds on population variance when constructing the confidence region

## Value

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
 ```1 2 3 4 5 6 7``` ```K <- 5 c0 <- 1 mu0 <- 0 tau2 <- 12.5 vi <- (seq(1, 5, length=K))^2 yi=rnorm(K)*sqrt(vi+tau2)+mu0 rma.exact.fast(yi=yi,vi=vi,level=.05) ```