t1way:

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

Usage

t1way(x, tr = 0.2, grp = NA, MAT = FALSE, lev.col = 1, var.col = 2, IV = NULL, pr = TRUE)

Arguments

x
tr
grp
MAT
lev.col
var.col
IV
pr

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 (x, tr = 0.2, grp = NA, MAT = FALSE, lev.col = 1, var.col = 2, 
    IV = NULL, pr = TRUE) 
{
    if (is.data.frame(x)) 
        x = as.matrix(x)
    if (tr == 0.5) 
        print("Warning: Comparing medians should not be done with this function")
    if (!is.null(IV[1])) {
        if (pr) 
            print("Assuming x is a vector containing all of the data, the dependent variable")
        xi = elimna(cbind(x, IV))
        x = fac2list(xi[, 1], xi[, 2])
    }
    if (MAT) {
        if (!is.matrix(x)) 
            stop("With MAT=T, data must be stored in a matrix")
        if (length(lev.col) != 1) 
            stop("Argument lev.col should have 1 value")
        temp = selby(x, lev.col, var.col)
        x = temp$x
        grp2 = rank(temp$grpn)
        x = x[grp2]
    }
    if (is.matrix(x)) 
        x <- listm(x)
    if (is.na(sum(grp[1]))) 
        grp <- c(1:length(x))
    if (!is.list(x)) 
        stop("Data are not stored in a matrix or in list mode.")
    J <- length(grp)
    h <- vector("numeric", J)
    w <- vector("numeric", J)
    xbar <- vector("numeric", J)
    nv = NA
    for (j in 1:J) {
        xx <- !is.na(x[[j]])
        val <- x[[j]]
        x[[j]] <- val[xx]
        nv[j] = length(x[[j]])
        h[j] <- length(x[[grp[j]]]) - 2 * floor(tr * length(x[[grp[j]]]))
        if (winvar(x[[grp[j]]], tr) == 0) 
            print(paste("The Winsorized variance is zero for group", 
                j))
        w[j] <- h[j] * (h[j] - 1)/((length(x[[grp[j]]]) - 1) * 
            winvar(x[[grp[j]]], tr))
        xbar[j] <- mean(x[[grp[j]]], tr)
    }
    u <- sum(w)
    xtil <- sum(w * xbar)/u
    A <- sum(w * (xbar - xtil)^2)/(J - 1)
    B <- 2 * (J - 2) * sum((1 - w/u)^2/(h - 1))/(J^2 - 1)
    TEST <- A/(B + 1)
    nu1 <- J - 1
    nu2 <- 1/(3 * sum((1 - w/u)^2/(h - 1))/(J^2 - 1))
    sig <- 1 - pf(TEST, nu1, nu2)
    list(TEST = TEST, nu1 = nu1, nu2 = nu2, n = nv, p.value = sig)
  }

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