Equivalence testHello
I want to compare two analytical methods that measure the purity of my samples and prove they are equivalent. I know they don't provide the exact same results which means the mean of their difference is not 0. However, I only need to prove that the difference between their results is less than 2%. My data are based on 28 different samples and each sample was analyzed once by each method. We tested the equivalence with a two-sided t-test on the purity difference but we are not sure this test is the most appropriate to prove the concept. Please not that the data is not normally distributed. Can someone please advise on this?
AnalyticsData TableRe: Equivalence testHi @CentroidJackal1 ,
The way you present and propose is definitely one way to evaluate the data. One thing to keep in mind though, is that when you say the difference in the results need to be less than 2%, 2% of which one, method A or method B? This part was not well explained.
Another way to look at the data might be with a mean-difference plot, much like a Bland-Altman analysis. You can read up on it from the link. This is a good way to evaluate if two different methods are essentially equivalent and to see if there's any bias in the data and if it's coming from one method versus another. The BA analysis doesn't require normally distributed data.
Hope this helps!,
DS
Re: Equivalence testThere are numerous long-standing standards (e.g., NCCLS, IUPAC, ICH) about method comparison. It can involve a number of aspects of the measurement: accuracy, precision, linearity, limit of detection or quantitation, and so on. You can using Fit Orthogonal command in Bivariate to perform a Deming regression that minimizes the error in X and Y. JMP 17 will also include Passing-Bablok regression and Bland-Altman analysis. In the meantime, see the JMP Help chapter about Measurement System Analysis for more ideas.
