mf <- model.frame(formula)
    }
    else {
        mf <- model.frame(formula, data)
    }
    cl <- match.call()
    xy <- split(model.extract(mf, "response"), mf[, 2])
    faclevels <- names(xy)
    x <- xy[[1]]
    y <- xy[[2]]
    if (tr == 0.5)
        warning("Comparing medians should not be done with this function!")
    alpha <- 0.05
    if (is.null(y)) {
        if (is.matrix(x) || is.data.frame(x)) {
            y = x[, 2]
            x = x[, 1]
        }
        if (is.list(x)) {
            y = x[[2]]
            x = x[[1]]
        }
    }
    if (tr > 0.25)
        print("Warning: with tr>.25 type I error control might be poor")
    x <- x[!is.na(x)]
    y <- y[!is.na(y)]
    h1 <- length(x) - 2 * floor(tr * length(x))
    h2 <- length(y) - 2 * floor(tr * length(y))
    q1 <- (length(x) - 1) * winvar(x, tr)/(h1 * (h1 - 1))
    q2 <- (length(y) - 1) * winvar(y, tr)/(h2 * (h2 - 1))
    df <- (q1 + q2)^2/((q1^2/(h1 - 1)) + (q2^2/(h2 - 1)))
    crit <- qt(1 - alpha/2, df)
    dif <- mean(x, tr) - mean(y, tr)
    low <- dif - crit * sqrt(q1 + q2)
    up <- dif + crit * sqrt(q1 + q2)
    test <- abs(dif/sqrt(q1 + q2))
    yuen <- 2 * (1 - pt(test, df))
    result <- list(test = test, conf.int = c(low, up), p.value = yuen,
        df = df, diff = dif, call = cl)
    class(result) <- "yuen"
    result
}