This question already has an answer here:
I have some data on a drug where doctors are trying to find out based on collected data how many patients get heart disease because of a drug.
The output is the following:
95%CI 1.72(1.28-2.30) for the patients are taking this drug
95%CI 1.30(1.21-1.40) for the patients which are not taking the drug
Therefore we conclude that there is a 42% absolute increase for getting the heart disease compared to the no users. I think I’m right here?
Back to the CI-95%,, does this mean that if the study was repeated with another sample and the parameters being the same (age, sex, other diseases, other medications taken) that 95% out of the sample (let’s say a sample of 100 people which would then be 95 patients) would show the same amount of people getting the heart disease? Is this what the CI is all about? Because if we take a random sample but not with the same parameters values (age, sex, other diseases, other medications) we wouldn't get even close to the 95% we would have a 20% match or so..
In essence would the other sample yield the result of 95% of the patients being in the 1.28-2.30 interval and the other 5 % being outside of the interval?