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