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## Main Question or Discussion Point

Hi everyone,

I'm trying to find a test to compare two assays, and I'm not sure which one I should use. Could you please help?

Here's the situation.

My company is setting up two assays,

Both assays are supposed to measure the same property of certain items, i.e. we would expect

We plan to test

However, we can only run either

We are therefore trying to measure if and to what extent

The plan is to select a random subset of the 100000 items, say 5000, run both

How would you analyse this?

I was thinking of using the concordance correlation coefficient (CCC), or maybe the rank correlation coefficient.

Is this appropriate?

And if so, can a significance be calculated for these coefficients, like there is one for the 'standard' linear correlation coefficient?

My other question is: are 5000 items out of 100000 sufficient to give us enough confidence in the 'agreement' that we observe?

E.g. how would we calculate the minimal number

Thank you!

L

I'm trying to find a test to compare two assays, and I'm not sure which one I should use. Could you please help?

Here's the situation.

My company is setting up two assays,

**A**and**B**.Both assays are supposed to measure the same property of certain items, i.e. we would expect

**A**and**B**to give broadly the same value of the property when applied to the same item.We plan to test

**N**=100000 items.However, we can only run either

**A**or**B**on all of these items, because running both is too expensive.**A**is considered less accurate, but is also less expensive than**B**, so if there is enough 'agreement' between**A**and**B**, we would prefer to run**A**.We are therefore trying to measure if and to what extent

**A**and**B**are 'agreeing'.The plan is to select a random subset of the 100000 items, say 5000, run both

**A**and**B**on them and compare the results, in particular looking at whether the same items did indeed give broadly the same assay result in both assays.How would you analyse this?

I was thinking of using the concordance correlation coefficient (CCC), or maybe the rank correlation coefficient.

Is this appropriate?

And if so, can a significance be calculated for these coefficients, like there is one for the 'standard' linear correlation coefficient?

My other question is: are 5000 items out of 100000 sufficient to give us enough confidence in the 'agreement' that we observe?

E.g. how would we calculate the minimal number

**n**of items to pre-test in both assays to reach a significance p<0.05? But in fact, isn't the significance related to the actual coefficient, which one doesn't know before, so how is it even possible to estimate**n**?Thank you!

L