rma.exact.fast {rma.exact} | R Documentation |
Compute a confidence interval for the grand mean at a user-specified confidence level.
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)