# Is the ICC appropriate here?

I have N tissue samples, labelled as either A or B. 2 measurements are taken from each sample.

The data is not normally distributed.

I'm interested in 2 things: firstly, whether there is significant difference between the means of the 2 classes A and B (treating the repeated measures as independent data instances). This seems simple enough.

However I'm also interested to know how well the 2 measurements taken from each sample tend to agree. This sounds like intra-class coefficient to me, however each "class" in this case only contains the 2 repeated measures.

Would the stndard calculation of ICC suffice here? Should I repeat the test independently for the groups A and B or can I lump them together?

Thanks so much, I hope this isn't too basic. let me know if I can provide any other information.

• When you say the data are not normal, is this known a-priori e.g. the data cannot be negative? If not, how non-normal are the data? The following histograms: A data (n = N), B data (n = N) and the N means of A and B for each case; are helpful? And what is the value of N? May 16 '19 at 16:37
• There isn't an obvious reason why the data shouldn't be normal, but the histograms don't appear to be. I was just hoping for a method that didn't require normality. For simplicity, let's say N=50, |A|=|B|=25. Then there are a total of 100 data points, 2 measurements for each element of A,B. I'm trying to keep things simple/abstract - I just want to know if ICC can be applied to a large number (50) of small (2) groups of data.
– Will
May 16 '19 at 17:58
• What is wrong with a simple correlation coefficient in place of the ICC? May 16 '19 at 18:11
• Ok I guess it was a dumb question and the ICC does apply. I guess I'd only seen ICC used when the data are organized into a smaller number of large groups, but I guess there's no reason why it shouldn't extend to my case
– Will
May 16 '19 at 18:18
– Will
May 16 '19 at 18:20