Timeline for Which test for association between two repeat categorical variables?
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| Sep 7, 2018 at 20:38 | comment | added | Nuclear Hoagie | You could first build the contingency table of Students by Strategies, and see if there's any association there. If different students don't prefer different strategies, then I think it might be OK to treat a single student's strategy selections as independent over the 4 questions, in which case the simple chi-square would be sufficient. Although there are ways to model this student-strategy dependence more directly, without showing/assuming their independence. | |
| Jul 7, 2018 at 1:10 | answer | added | BelwarDissengulp | timeline score: 0 | |
| Oct 2, 2017 at 17:22 | comment | added | alexeymosco | Not exactly. You are going to literally measure if the Strategy variable depends significantly on the Type variables. I suppose you have data as follows: line 1: student John, Strategy 1, Type 2; line 2: student Mary, Strategy 3, Type 4, etc. So the first question is making sure that there is not dependency between the lines, for all the variables. It could be be if, for example, the first half of the test was performed by students who are friend and they share results, but the second half was run on randomly chosen students. | |
| Oct 2, 2017 at 17:14 | comment | added | user141002 | @AlexBurn Do you mean dividing students into 4 groups and each group work on one question type? | |
| Oct 2, 2017 at 17:10 | comment | added | alexeymosco | Having i.i.d. observations is a must have in any test of association you are going to run. I suggest measuring a dependance in your data, trying to get over it (by subsampling, for example), and using the Chi-Square statistics. | |
| S Oct 2, 2017 at 16:16 | history | suggested | Giuseppe Biondi-Zoccai | CC BY-SA 3.0 |
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| Oct 2, 2017 at 16:14 | review | Suggested edits | |||
| S Oct 2, 2017 at 16:16 | |||||
| Oct 2, 2017 at 14:36 | comment | added | IWS | I think you are right to assume a standard chi-square test might not tell the whole story. I do not know whether this is true in your case, but AFAIK, you seem to be suggesting that your data is generated by a structure where measurements within students might be linked (i.e. non-independent). This is sometimes called a multi-level structure or random-effects model, where each level can explain some of the variance. This is clear-cut for continuous variables, but less so for categorical ones. I feel you should look at generalized mixed models with multinomial outcomes. | |
| Oct 2, 2017 at 12:58 | history | asked | user141002 | CC BY-SA 3.0 |