I am using JMP version 16.1 and working on comparing a nonlinear standard curve (ID- STD) against 3 other nonlinear curves (ID- Set A, B, C) to see if they are similar.
What I did was plotting the 4 curves using analyze>specialized model>nonlinear set up as attached. After that I select logistic 4P and perform Parallelism test and Equivalence test. The p-value obtained is 0.0056 which is below 0.05 and all stats in equivalence test does not match the STD curve. Thus, I am right to say these 4 curves are not comparable?
However, I did a normalization of the results and did the same test but this time round I select logistic 2P for the curve and I got a P-value of 0.6794 which shows 4 curves are comparable but the stats in equivalence test does not match the STD curve. Thus, I am quite lost of the data I have and not too sure how to interpret it.
Any advice would be great. Thank you.
I have attached the data I use for the study.
First of all, the choice of the Logistic 4P model is overly optimistic. There is only the lower asymptote and no inflection point, so you won't have a good estimate of the upper asymptote for comparison. This situation also leads to unstable estimates for all the parameters.
Second, why use a complicated non-linear model for this data? A plot of result obtained versus concentration appears to be linear. The Fit Curve platform can fit such models and assess them for parallelism, too.
