cidmulv2:
In musto101/wilcox_R: What the package does (short line)

Usage Arguments Examples

1	cidmulv2(x, alpha = 0.05, g = NULL, dp = NULL, CI.FWE = FALSE)

`x`
`alpha`
`g`
`dp`
`CI.FWE`

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x, alpha = 0.05, g = NULL, dp = NULL, CI.FWE = FALSE) 
{
    if (!is.null(g)) {
        if (is.null(dp)) 
            stop("Specify a value for dp, the column containing the data")
        x = fac2list(x[, dp], x[, g])
    }
    if (is.data.frame(x)) 
        x = as.matrix(x)
    if (is.matrix(x)) 
        x <- listm(x)
    if (!is.list(x)) 
        stop("Data must be stored in a matrix or in list mode.")
    J <- length(x)
    CC <- (J^2 - J)/2
    test <- matrix(NA, CC, 7)
    c.sum = matrix(NA, CC, 5)
    for (j in 1:J) {
        xx <- !is.na(x[[j]])
        val <- x[[j]]
        x[[j]] <- val[xx]
    }
    dimnames(test) <- list(NULL, c("Group", "Group", "p.hat", 
        "p.ci.lower", "p.ci.uppper", "p-value", "p.crit"))
    dvec <- alpha/c(1:CC)
    dimnames(c.sum) <- list(NULL, c("Group", "Group", "P(X<Y)", 
        "P(X=Y)", "P(X>Y)"))
    jcom <- 0
    n = matl(lapply(x, length))
    for (j in 1:J) {
        for (k in 1:J) {
            if (j < k) {
                temp <- cidv2(x[[j]], x[[k]], alpha, plotit = FALSE)
                jcom <- jcom + 1
                test[jcom, 1] <- j
                test[jcom, 2] <- k
                c.sum[jcom, 1] <- j
                c.sum[jcom, 2] <- k
                c.sum[jcom, 3:5] = cid(x[[j]], x[[k]])$summary.dvals
                test[jcom, 3] <- temp$p.hat
                test[jcom, 4] <- temp$p.ci[1]
                test[jcom, 5] <- temp$p.ci[2]
                test[jcom, 6] <- temp$p.value
            }
        }
    }
    temp2 <- order(0 - test[, 6])
    test[temp2, 7] = dvec
    if (CI.FWE) {
        jcom <- 0
        for (j in 1:J) {
            for (k in 1:J) {
                if (j < k) {
                  jcom <- jcom + 1
                  temp <- cidv2(x[[j]], x[[k]], alpha = test[jcom, 
                    7], plotit = FALSE)
                  test[jcom, 4] <- temp$p.ci[1]
                  test[jcom, 5] <- temp$p.ci[2]
                }
            }
        }
    }
    list(n = n, test = test, summary.dvals = c.sum)
  }