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# This is a modified version of https://github.com/jcfaria/ScottKnott/blob/master/R/SK.aov.R which is originally written by Jose Claudio Faria
# Change Notes:
# - Add an 'av' arguemtn for the partition() function
scottknott <- function(x,
which=NULL,
id.trim=3,
sig.level=.05,
dispersion=c('mm', 's', 'se'), ...)
{
if(is.null(which))
which <- names(x$model)[2]
mt <- model.tables(x, "means") # summary tables for model fits
if(is.null(mt$n))
stop("No factors in the fitted model!")
r <- mt$n[names(mt$tables)][[which]] # groups and its number of replicates
MSE <- deviance(x)/df.residual(x)
m <- as.vector(mt$tables[[which]]) # means
nms <- names(mt$tables[[which]])
ord <- order(m, decreasing=TRUE)
m.inf <- m.inf.1a(x,
which,
dispersion)
rownames(m.inf) <- nms
m.inf <- m.inf[order(m.inf[,1],
decreasing=TRUE),]
mMSE <- MSE / r
dfr <- x$df.residual # residual degrees of freedom
g <- nrow(m.inf)
groups <- Partition(g,
m.inf[, 1],
mMSE,
dfr,
sig.level=sig.level,
av=x,
1,
rep(0, g),
0,
rep(0, g))
res <- list(av=x,
groups=groups,
nms=nms,
ord=ord,
m.inf=m.inf,
sig.level=sig.level)
class(res) <- c('sk_esd',
'list')
invisible(res)
}
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