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

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

See Also

rma.exact for computing entire confidence regions

Examples

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)

rma.exact documentation built on May 1, 2019, 10:24 p.m.