R/hMeanChiSq.R

In ReplicationSuccess: Design and Analysis of Replication Studies

## harmonic mean chi-squared test based on z-values

hMeanChiSq <- function(z, w = rep(1, length(z)), alternative = "greater", bound=TRUE){
    stopifnot(min(w) > 0)
    if (!(alternative %in% c("greater", "less", "two.sided", "none")))
        stop('alternative must be either "greater", "less", "two.sided" or "none"')
    n <- length(z)
    zH2 <- sum(sqrt(w))^2/sum(w/z^2)
    res <- pchisq(zH2, df = 1, lower.tail = FALSE)
    check.greater <- (min(z) > 0)
    check.less <- (max(z) < 0)
    break.p <- 1/(2^n)
    if(alternative == "greater"){
        if(bound == TRUE)
            res <- ifelse(check.greater, res/(2^n), paste(">", format(break.p, scientific = FALSE)))
        if(bound == FALSE)
            res <- ifelse((check.greater | check.less), res/(2^n), NA)
    }
    if(alternative == "less"){
        if(bound == TRUE)
            res <- ifelse(check.less, res/(2^n), paste(">", format(break.p, scientific = FALSE)))
        if(bound == FALSE)
            res <- ifelse((check.greater | check.less), res/(2^n), NA)
    }
    if(alternative == "two.sided"){
        if(bound == TRUE)
            res <- ifelse((check.greater | check.less), res/(2^(n-1)), paste(">", format(2*break.p, scientific = FALSE)))
        if(bound == FALSE)
            res <- ifelse((check.greater | check.less), res/(2^(n-1)), NA)
    }
    if(alternative == "none"){
        res <- res
    }    
    return(res)
}