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#' Test Statistics for One-Way Layout Permutation Test
#'
#' \code{owlStat} computes statistics for \code{owl}. This is not meant to be
#' called directly.
#'
#' @param lov a list of vectors, responses by experimental groups.
#' @param env an environment, to access outer scope variables.
#'
#' @return \code{owlStat} returns a list with 5 components: \item{\code{n}}{the
#' sample sizes.} \item{\code{avg}}{the mean responses.} \item{\code{T}}{the T
#' statistic for global test.} \item{\code{d.multi}}{the differences in means
#' for multiple comparisons.} \item{\code{mad}}{the maximum absolute
#' differences in means.}.
#'
#' @references Ernst, M. D. (2004). Permutation Methods: A Basis for Exact
#' Inference. Statistical Science, 19(4), 676–685.
#' \doi{10.1214/088342304000000396}.
#'
#' @export
owlStat <-
function(lov, env = parent.frame()) {
#input a list of vectors
n <- sapply(lov, length)
avg <- sapply(lov, mean)
T <- n %*% avg ^ 2 %>% as.numeric()
if (env$type.post == "all")
d.multi <- outer(avg, avg, "-") #pairwise differences in means
if (env$type.post == "control")
d.multi <-
avg[-1] - avg[1] #differences in means compared to the control
mad <-
d.multi %>% abs() %>% max() #max absolute differences in means
list(
n = n,
avg = avg,
T = T,
d.multi = d.multi,
mad = mad
)
}
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