conversion {ANOFA}

Converting between formats

Description

The functions toWide(), toLong(), toCompiled() toRaw() and toTabular() converts the data into various formats.

Usage

toWide(w)

toLong(w)

toCompiled(w)

toRaw(w)

toTabular(w)

Arguments

w

An instance of an ANOFA object.

Details

The classification of a set of $n$ participants can be given using many formats. One basic format (called wide herein) has $n$ lines, one per participants, and category names assigned to each. Another format (called compiled herein) is to have a list of all the categories and the number of participants falling in each cells. This last format is typically much more compact (if there are 6 categories, the data are all contained in six lines). However, we fail to see each individual contributing to the counts. See the vignette DataFormatsForFrequencies for more. A third possible format (called raw herein) put one column per category and 1 is the observation matches this category, 0 otherwise. This format results in $n$ lines, one participants, and as many columns are there are categories. Lastly, a fourth format (called long herein) as, on a line, the factor name and the category assigned in that factor. If there are $f$ factors and $n$ participants, the data are in $f*n$ lines.

See the vignette DataFormatsForFrequencies for more.

Value

a data frame in the requested format.

Examples

# The minimalExample contains $n$ of 20 participants categorized according
# to two factors $f = 2$, namely `Intensity` (three levels) 
# and Pitch (two levels) for 6 possible cells.
minimalExample

# Lets incorporate the data in an anofa data structure
w <- anofa( Frequency ~ Intensity * Pitch, minimalExample )

# The data presented using various formats looks like
toWide(w)
# ... has 20 lines ($n$) and 2 columns ($f$)

toLong(w)
# ... has 40 lines ($n \times f$) and 3 columns (participant's `Id`, `Factor` name and `Level`)

toRaw(w)
# ... has 20 lines ($n$) and 5 columns ($2+3$)

toCompiled(w)
# ... has 6 lines ($2 \times 3$) and 3 columns ($f$ + 1)

toTabular(w)
# ... has one table with $2 \times 3$ cells. If there had been
# more than two factors, the additional factor(s) would be on distinct layers.