>From a somewhat ill-designed education experiment, I have categorical data with two between subject variables and one within subject variable. Since it is categorical (essentially counts of answer choices on multiple choice questions), I'm looking for some chi-squared method.
I know how to generalize Pearson's chi-square for n between subject dimensions, and I know McNemar's test for a within subject factor, but how can I mix these methods? Also, I need to be able to do post-hoc comparisons in all dimensions. Any ideas or references? I'd be happy to share more details as needed. Here is a sample from the data. All together, there are 366 subjects. There are 4 levels of Test_no (1,2,3,4), Ans1 and Ans2 are the within subject measures, and there are 8 levels of Ans* (cor, SE, CP, CPSE, FoM, FoMSE, zero, other). Thanks, again! SID Test_No Ans1 Ans2 1 1 other other 2 1 CPSE CP 3 1 other other 4 1 SE SE 5 1 FoM CP 6 1 FoM CPSE 7 2 cor cor 8 2 cor cor 9 2 cor cor 10 2 CPSE CPSE 11 2 cor cor 12 2 CPSE cor 13 2 CPSE cor 14 3 CP cor 15 3 cor cor 16 3 CP FoM 17 3 cor cor 18 3 cor cor 19 3 zero other 20 3 SE CP 21 3 SE FoM 22 3 CP CP 23 4 zero SE 24 4 CPSE cor 25 4 SE cor 26 4 CP CP 27 4 SE cor 28 4 SE SE 29 4 CPSE cor I would like to be able to compare different answers within a test, and how answers are different for different tests. -- View this message in context: http://www.nabble.com/analysis-of-categorical-data-tp25140738p25140738.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.
