I'm looking to check my logic here.
Say you measure a quantity in group A, and find the mean is 2 and your 95% confidence interval ranges from 1 to 3. Then you measure the same quantity in group B and find a mean of 4 with a 95% confidence interval that ranges from 3.5 to 4.5. Assuming that A & B are independent, what is the 95% confidence interval for the difference between the groups? Presumably you can compute this using standard t-statistics, but I'd like to know if it's also possible to compute an estimate based on the CI's alone.
I reason that the lower bound of the CI of the difference should be the minimum credible difference between A & B; that is, the lower bound of the interval for B (3.5) minus upper bound of the interval for A (3), which yields a lower bound for the difference of 0.5. Similarly, the upper bound of the CI of the difference should be the maximum credible difference between A & B; that is, the upper bound of the interval for B (4.5) minus lower bound of the interval for A (1), which yields a lower bound for the difference of 3.5. This reasoning thus yields a confidence interval for the difference that ranges from 0.5 to 3.5.
Does that make sense, or is this a case where logic and statistics diverge?