Hello,
If the output of ftable is kept in an object named 'ft', try this.
ftperc <- t(apply(ft, 1, function(x)
if(sum(x)) round(100*x/sum(x)) else rep(0, length(x))))
attributes(ftperc) <- attributes(ft)
ftperc
(And if you need it to process several datasets, a function with 'ft' as
the argument and the code above as its body is straightforward to write.)
Hope this helps,
Rui Barradas
Em 13-05-2012 11:00, r-help-requ...@r-project.org escreveu:
Date: Sat, 12 May 2012 14:00:03 -0700 (PDT)
From: cassiorx<cassiodo...@hotmail.com>
To:r-help@r-project.org
Subject: [R] categorical analysis - grouping rows
Message-ID:<1336856403964-4629503.p...@n4.nabble.com>
Content-Type: text/plain; charset=us-ascii
I apologize up front if this has been covered elsewhere - but I can't find
any such question.
I have a data set that contains academic data: term (i.e., semester),
student id, dept, class, success (1=Y, 0=N)
I want to look at dept by term to determine descriptive statistics for
success to failure ratios. The intent being to discover if there are
departments that contribute significantly to the Simpson Paradox, that is,
that make overall success/failure rates undependable.
It's easy to use ftable to get the counts for what I need (row names dept
and success, col name success. So I get something that looks like this:
Term 1st 2nd 3rd 4th 5th
dept success
AAA 0 155 240 163 286 293
1 424 570 349 582 429
AAB 0 55 64 103 46 109
1 122 117 145 112 145
AAC 0 11 3 4 4 4
1 19 12 23 11 7
How can I calculate percentages by dept so that I get
AAA 0 27 ....
1 73 ....
AAB 0 ...
Part of my lack of understanding is that I don't see a way to get the dept
(by term) totals into a data structure that I can use to calculate the
percentages. I can write procedural code to do this but is there some r-way
that would be better?
--
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