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? -- View this message in context: http://r.789695.n4.nabble.com/categorical-analysis-grouping-rows-tp4629503.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.