- Thread starter jacob
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Odds Ratio Estimates and Profile-Likelihood Confidence Intervals

Moderate vs Mild: 1.596 (95% CI: 0.276, 24.059)

Severe vs Mild: 0.319 (95% CI: 0.049, 2.710)

No linear trend in outcome when looking mild to severe exposure levels.

Next do the following (A times D) / (B times C), that is the odds ratio for that table. You will also want to add 95% confidence intervals to it. Once you do the above post your answers and we can talk about the CIs.

And no one outside a university course will every do that

I did not know about the bonferoni correction.

(But he was a person, so should he not be spelled with an upper case B in English?)

The CI will tell you if the results are significant. They won't tell you what the specific p value is.

When I said no one used this approach I meant no one manually calculated odds ratios and p values. They normally use a computer. Only in classes do you do things like manually calculate these.

Its interesting that the CI is considered more informative. In the journals I have read in the social sciences it is the p value that was stressed, the CI rarely gets mentioned. But my real point is the OP wanted to know a p value not a CI. Calculating a P value by hand would be really really hard.

Bonferoni probably should be capitalized. But I don't think it usually is much like firth is not.

Apparently without eyebrows?

But what about Firth? He was a person too. Don't you have love for him?

GretaGarbo I knew about the bonferoni correction. I did not know it was used as hlsmith used it.

When I said no one used this approach I meant no one manually calculated odds ratios and p values. They normally use a computer. Only in classes do you do things like manually calculate these.

Its interesting that the CI is considered more informative. In the journals I have read in the social sciences it is the p value that was stressed, the CI rarely gets mentioned. But my real point is the OP wanted to know a p value not a CI. Calculating a P value by hand would be really really hard.

Of course a CI can be calculated from a series of tests - all the values outside of the CI can be rejected with the test, and all values within the CI can not be rejected. So in that sense CI:s and test contain the same information (there is a correspondence theorem). But people does not misunderstand the CI:s as much as p-values.

And you are right the original poster asked for p-values.