bwimcpES:

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

Usage

bwimcpES(J, K, x, tr = 0.2, JK = J * K, grp = c(1:JK), alpha = 0.05, SEED = TRUE)

Arguments

J
K
x
tr
JK
grp
alpha
SEED

Examples

##---- 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 (J, K, x, tr = 0.2, JK = J * K, grp = c(1:JK), alpha = 0.05, 
    SEED = TRUE) 
{
    if (is.matrix(x)) {
        y <- list()
        for (j in 1:ncol(x)) y[[j]] <- x[, j]
        x <- y
    }
    JK <- J * K
    if (JK != length(x)) 
        stop("Something is wrong. Expected ", JK, " groups but x contains ", 
            length(x), "groups instead.")
    MJ <- (J^2 - J)/2
    MK <- (K^2 - K)/2
    JMK <- J * MK
    MJMK <- MJ * MK
    Jm <- J - 1
    data <- list()
    for (j in 1:length(x)) {
        data[[j]] <- x[[grp[j]]]
    }
    x <- data
    output <- matrix(0, MJMK, 9)
    dimnames(output) <- list(NULL, c("A", "A", "B", "B", "psihat", 
        "p.value", "p.crit", "EF.xi", "EF.WMW"))
    jp <- 1 - K
    kv <- 0
    kv2 <- 0
    test <- NA
    for (j in 1:J) {
        jp <- jp + K
        xmat <- matrix(NA, ncol = K, nrow = length(x[[jp]]))
        for (k in 1:K) {
            kv <- kv + 1
            xmat[, k] <- x[[kv]]
        }
        xmat <- elimna(xmat)
        for (k in 1:K) {
            kv2 <- kv2 + 1
            x[[kv2]] <- xmat[, k]
        }
    }
    m <- matrix(c(1:JK), J, K, byrow = T)
    ic <- 0
    for (j in 1:J) {
        for (jj in 1:J) {
            if (j < jj) {
                for (k in 1:K) {
                  for (kk in 1:K) {
                    if (k < kk) {
                      ic <- ic + 1
                      output[ic, 1] <- j
                      output[ic, 2] <- jj
                      output[ic, 3] <- k
                      output[ic, 4] <- kk
                      x1 <- x[[m[j, k]]] - x[[m[j, kk]]]
                      x2 <- x[[m[jj, k]]] - x[[m[jj, kk]]]
                      temp <- yuenv2(x1, x2, SEED = SEED)
                      output[ic, 5] <- mean(x1, tr) - mean(x2, 
                        tr)
                      test[ic] <- temp$p.value
                      output[ic, 6] <- test[ic]
                      output[ic, 8] <- temp$Effect.Size
                      output[ic, 9] = cid(x1, x2)$summary.dvals[1]
                    }
                  }
                }
            }
        }
    }
    ncon <- length(test)
    dvec <- alpha/c(1:ncon)
    temp2 <- order(0 - test)
    zvec <- dvec[1:ncon]
    sigvec <- (test[temp2] >= zvec)
    output[temp2, 7] <- zvec
    output[, 7] <- output[, 7]
    output
  }

musto101/wilcox_R documentation built on May 23, 2019, 10:52 a.m.