Timeline for How do I test for independence with non-exclusive categorical variables?
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| Apr 13, 2016 at 6:48 | answer | added | Erosennin | timeline score: 1 | |
| Apr 13, 2016 at 6:26 | comment | added | tschoppi | @Erosennin: There is no fixed number of trials (may be design error on my part, but now I have to live with it). So what you're saying is that I can use poisson regression with interaction to model my data. But the interpretation would be tricky, no? | |
| Apr 13, 2016 at 6:26 | comment | added | Erosennin | @Scortchi Ah, I get it! Yes, that was my thought | |
| Apr 13, 2016 at 6:14 | comment | added | Scortchi♦ | @Erosennin: Sorry, I'll retract that. I was assuming a binomial sampling scheme in which the no. trials for each person is fixed; you're perhaps thinking of two independent observations of a Poisson count for each person. | |
| Apr 12, 2016 at 19:44 | comment | added | Erosennin | @tschoppi you write: "Now, I want to assign (by hand) classes to these people, and then test if the output depends on one of the classes. My problem is that the classes, while not necessarily dependent on each other, are not exclusive. The classes can however be dependent on each other.". The fact that they are exclusive you could solve by making them interact with each other when specifying the poisson regression. If I'm not completely off track here misunderstanding your data and question | |
| Apr 12, 2016 at 19:41 | comment | added | Erosennin | @Scortchi Could you elaborate on that independency statement? Could they not be independent because they occur at the same time? | |
| Apr 12, 2016 at 16:16 | comment | added | Scortchi♦ | If "outcome1 does not occur at the same time as outcome2", they are certainly not independent. It would help to explain the context - exactly what observations are you making for each person? | |
| Apr 12, 2016 at 15:01 | comment | added | tschoppi | Yes, outcome1 and outcome2 are independent. | |
| Apr 12, 2016 at 14:38 | comment | added | Erosennin | outcome1 and outcome2 are independent as well? You only say they do not happen at the same time. I imagine you could do poisson regression here, if you want to measure the dependence of multiple variables on the outcome. But this could be a problem if your explanatory variables are very dependent. | |
| Apr 12, 2016 at 13:57 | review | First posts | |||
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| Apr 12, 2016 at 13:57 | history | asked | tschoppi | CC BY-SA 3.0 |