R/ctb.R

In phia: Post-Hoc Interaction Analysis

# Functions from stats that cannot be imported (used in summary.testFactors.mlm)

stats_Pillai <- function (eig, q, df.res) 
{
    test <- sum(eig/(1 + eig))
    p <- length(eig)
    s <- min(p, q)
    n <- 0.5 * (df.res - p - 1)
    m <- 0.5 * (abs(p - q) - 1)
    tmp1 <- 2 * m + s + 1
    tmp2 <- 2 * n + s + 1
    c(test, (tmp2/tmp1 * test)/(s - test), s * tmp1, s * tmp2)
}

stats_Wilks <- function (eig, q, df.res) 
{
    test <- prod(1/(1 + eig))
    p <- length(eig)
    tmp1 <- df.res - 0.5 * (p - q + 1)
    tmp2 <- (p * q - 2)/4
    tmp3 <- p^2 + q^2 - 5
    tmp3 <- if (tmp3 > 0) 
        sqrt(((p * q)^2 - 4)/tmp3)
    else 1
    c(test, ((test^(-1/tmp3) - 1) * (tmp1 * tmp3 - 2 * tmp2))/p/q, 
        p * q, tmp1 * tmp3 - 2 * tmp2)
}

stats_HL <- function (eig, q, df.res) 
{
    test <- sum(eig)
    p <- length(eig)
    m <- 0.5 * (abs(p - q) - 1)
    n <- 0.5 * (df.res - p - 1)
    s <- min(p, q)
    tmp1 <- 2 * m + s + 1
    tmp2 <- 2 * (s * n + 1)
    c(test, (tmp2 * test)/s/s/tmp1, s * tmp1, tmp2)
}

stats_Roy <- function (eig, q, df.res) 
{
    p <- length(eig)
    test <- max(eig)
    tmp1 <- max(p, q)
    tmp2 <- df.res - tmp1 + q
    c(test, (tmp2 * test)/tmp1, tmp1, tmp2)
}