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### Function to test null hypothesis of no effect
testeffect_nsig <- function(yi, vi, est, tau.est, ycv, method, con)
{
if (method == "ML")
{ # Conduct likelihood-ratio test
### Log-likelihood when estimating both parameters
ll <- ml_star(par = c(est, tau.est), yi = yi, vi = vi, ycv = ycv)
### Log-likelihood when average effect size is constrained to zero
ll0 <- optimize(f = ml_star_tau, interval = con$tau.int, d = 0, yi = yi, vi = vi,
ycv = ycv, maximum = TRUE)$objective
### Conduct likelihood-ratio test
L.0 <- -2*(ll0-ll)
pval.0 <- pchisq(L.0, df = 1, lower.tail = FALSE)
} else if (method == "P" | method == "LNP")
{
L.0 <- pval.0 <- NA
}
return(data.frame(L.0 = L.0, pval.0 = pval.0))
}
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