plot.mult {Kmisc}R Documentation

~~function to do ... ~~

Description

~~ A concise (1-5 lines) description of what the function does. ~~

Usage

plot.mult(x, col = 1:ncol(x), mid = TRUE, pch = "x", ...)

Arguments

x ~~Describe x here~~
col ~~Describe col here~~
mid ~~Describe mid here~~
pch ~~Describe pch here~~
... ~~Describe ... here~~

Details

~~ If necessary, more details than the description above ~~

Value

~Describe the value returned If it is a LIST, use

comp1 Description of 'comp1'
comp2 Description of 'comp2'

...

Warning

....

Note

~~further notes~~

~Make other sections like Warning with section{Warning }{....} ~

Author(s)

~~who you are~~

References

~put references to the literature/web site here ~

See Also

~~objects to See Also as help, ~~~

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, col=1:ncol(x), mid=TRUE, pch="x", ...) {
  names(col) <- colnames(x)
  x <- exclui.na(x)
  col <- col[is.element(names(col), colnames(x))]
  print(col)
  if (is.null(dim(x)))
    return(NA)
  x[is.na(x)] <- 0
  nr <- nrow(x)
  nc <- ncol(x)
  bt <- apply(x, 1, function(x) lapply(x, binom.test, sum(x)))
  ici <- sapply(bt, lapply, function(x) x$conf.int[[1]])
  ics <- sapply(bt, lapply, function(x) x$conf.int[[2]])
  if (mid) {
    p <- sapply(bt, lapply, function(x) x$estimate)
    ic <- lapply(1:nr, function(x,m,i,s) cbind(Media=unlist(m[, x]), Inferior=unlist(i[, x]), Superior=unlist(s[, x])), p, ici, ics)
  }
  else
    ic <- lapply(1:nr, function(x,i,s) cbind(Inferior=unlist(i[, x]), Superior=unlist(s[, x])), ici, ics)
  barplot(unlist(x[1,]), col="white", border="white", ...)
  cloc <- ((1:nr)-mean(1:nr))/(2*nr)
  for (i in 1:nr) {
    arrows.ic((1:nc)*1.2-0.5+cloc[i], ic[[i]], col=col[i], mid=mid, pch=pch)
  }
  }

[Package Kmisc version 1.0 Index]