How strong/weak of a correlation is this?
Exposure No Yes Total FALSE 139 467 606 Disease TRUE 11 104 115 Total 150 571 721 OR = 2.81 Exact 95% CI = 1.45, 5.97 Chi-squared = 10.49, 1 d.f., P value = 0.001 Fisher's exact test (2-sided) P value = 0.001
How about this?
Exposure No Yes Total Disease FALSE 301 1232 1533 TRUE 0 17 17 Total 301 1249 1550 OR = Inf Exact 95% CI = 1, Inf Chi-squared = 4.14, 1 d.f., P value = 0.042 Fisher's exact test (2-sided) P value = 0.057
- Are there any better/other methods for calculating relative risk with a confidence interval for data like these?
- If there are other methods, what are their advantages/disadvantages?
So, the first one is pretty easy, we could say "we estimate that those with the exposure are 2.81 [1.45, 5.97] times more likely to have the disease (p=.001)". That sounds like a pretty strong finding. Surprisingly strong for the hypothesis I'm working with.
The second table doesn't work with the same formula, "we estimate that those with the exposure are infinitely more likely to have the disease [1, Inf], p < .05". What can be said about the second table? Shrug and say, "hrm, look at that, we are missing about 4 not exposed with the disease .. and there are none who have the disease who weren't exposed." I guess I already know the answers here. But, on the second table, I'm torn between thinking, "OMG, LOOK, UNEXPOSED HAVE 0, and p<.05!" and thinking, "that's interesting that that happened completely by chance". I guess that's when we say, "more research needed"?