I am working on a population-based study including two waves (baseline and follow-up).

My variable of interest is computed using the two waves, and is the difference in renal function between follow-up and baseline (Delta = follow-up - baseline).

Renal function normally declines over time, so values at follow-up are lower than those at baseline (hence Delta < 0, normally).

However, in the actual data, I have approximately 2/3 of values whose Delta < 0 (expected), and 1/3 of values with Delta > 0 (unexpected, but is likely due to the fact that renal function values are imprecisely measured, and the time difference between baseline and follow-up is short : 3-4 years on average).

I would like to point out the fact that I am not a statistician, but a life-scientist, working with life-scientists on this project. My other colleague (life-scientist as well) asked me whether it is possible to show that there is a difference in the "N" between those individuals whose Delta<0 (2/3 of the sample size), and those whose Delta>0 (1/3 of the sample size).

I was puzzled by this request and couldn't find a proper answer. If I take the distribution of the variable "Delta", its mean is negative, and the 95%CI doesn't include the 0, indicating that Delta is indeed negative.

However, I am wondering whether this unusual request might be realized (comparison of the 2/3 Delta <0 and 1/3 Delta > 0 in terms of "N"). Indeed, if there was NO DECLINE in renal function, Delta would be centered around zero, and approximately 1/2 would be positive and 1/2 would be negative (given the imprecision of the variable)...

Any comment/suggestion would be appreciated =)

Thanks

Dusan