DescTools (version 0.99.8.1)

Desc.flags: Describe a Set of Dichotomous Variables

Description

Dichotomous variables can easily be condensed in one graphical representation. Desc for a set of flags (=dichotomous variables) calculates the frequencies, a binomial confidence intervall and produces a kind of dotplot with error bars.

Usage

## S3 method for class 'flags':
Desc(x, i = 1, plotit = getOption("plotit", FALSE), ...)
Flags(x)

Arguments

x

a data.frame

i

plotit

...

Value

• no results are returned.

Details

Motivation for this function is, that dichotomous variable in general do not contain intense information. Therefore it makes sense to condense the description of sets of dichotomous variables.

See Also

Desc

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, i = 1, plotit = getOption("plotit", FALSE), ...) 
{
    cat(paste(rep("-", (as.numeric(options("width")) - 2)), collapse = ""), 
        "")
    cat("Multiple dichotomous variables")
    if (!is.null(attr(x, "label"))) 
        cat(":", strwrap(attr(x, "label"), indent = 2, exdent = 2), 
            sep = "")
    cat("")
    cat("Summary: 
", "total n: ", nrow(x), "", sep = "")
    d.sub <- x
    flags <- do.call(rbind, lapply(d.sub, function(z) {
        tab <- table(z)
        data.frame(val = names(tab[i]), abs = tab[i], BinomCI(tab[i], 
            sum(tab)))
    }))
    out <- data.frame(do.call(rbind, lapply(d.sub, function(x) cbind(NAs = sum(is.na(x)), 
        n = length(x) - sum(is.na(x))))), flags)
    out[, 5:7] <- apply(out[, 5:7], 2, FormatFix, after = 3)
    print(out, quote = FALSE)
    cat("")
    if (plotit) 
        PlotDesc(x)
  }