t1wayv2:

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

Usage

t1wayv2(x, tr = 0.2, grp = NA, MAT = FALSE, lev.col = 1, var.col = 2, nboot = 100, SEED = TRUE, pr = TRUE, IV = NULL, loc.fun = median)

Arguments

x
tr
grp
MAT
lev.col
var.col
nboot
SEED
pr
IV
loc.fun

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, 
    nboot = 100, SEED = TRUE, pr = TRUE, IV = NULL, loc.fun = median) 
{
    library(MASS)
    if (SEED) 
        set.seed(2)
    if (is.data.frame(x)) 
        x = as.matrix(x)
    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.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 (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)
    pts = NULL
    nval = 0
    for (j in 1:J) x[[j]] = elimna(x[[j]])
    for (j in 1:J) {
        val <- x[[j]]
        val <- elimna(val)
        nval[j] = length(val)
        pts = c(pts, val)
        x[[j]] <- val
        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)
    nv = lapply(x, length)
    chkn = var(nval)
    if (chkn == 0) {
        top = var(xbar)
        bot = winvarN(pts, tr = tr)
        e.pow = top/bot
    }
    if (chkn != 0) {
        vals = 0
        N = min(nval)
        xdat = list()
        for (i in 1:nboot) {
            for (j in 1:J) {
                xdat[[j]] = sample(x[[j]], N)
            }
            vals[i] = t1way.effect(xdat, tr = tr)$Var.Explained
        }
        e.pow = loc.fun(vals, na.rm = TRUE)
    }
    list(TEST = TEST, nu1 = nu1, nu2 = nu2, n = nv, p.value = sig, 
        Var.Explained = e.pow, Effect.Size = sqrt(e.pow))
  }

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