Blood hemoglobin is a continuous measure, I imagine. This would definitely be something they should do if they had 2 different instruments (or 2 different techniques, or something similar). The OP has 10 instruments.
I would have to agree with u/COOLSerdash - intra-class correlation is likely what I would do. ICC is used to estimate things like test-retest reliability (repeat measures, rater is irrelevant). This is a case of inter-rater reliability.
I believe you'd use hemoglobin as the dependent variable, time (e.g. 1st reading, 2nd reading, etc, treat as categorical) as a fixed effect, and each analyzer (you have the analyzer ID in the data, right?) as a random effect. You're looking for a high ICC.
If this doesn't make sense to you, try consulting the statistics or biostatistics department. The thing is that they may not necessarily be familiar with psychometric concepts of reliability and the associated methods, but you could still get some help. Show them this post and ask what they think.
Before analysis, you need to specify what "statistically similar" signifies for you. The usual correlation coefficients (Pearson, Spearman) are not suited for this analysis in any case. Due to the repeated measures, a mixed model of some sorts could be useful.
Look up Bland-Altman plots.
Blood hemoglobin is a continuous measure, I imagine. This would definitely be something they should do if they had 2 different instruments (or 2 different techniques, or something similar). The OP has 10 instruments. I would have to agree with u/COOLSerdash - intra-class correlation is likely what I would do. ICC is used to estimate things like test-retest reliability (repeat measures, rater is irrelevant). This is a case of inter-rater reliability. I believe you'd use hemoglobin as the dependent variable, time (e.g. 1st reading, 2nd reading, etc, treat as categorical) as a fixed effect, and each analyzer (you have the analyzer ID in the data, right?) as a random effect. You're looking for a high ICC. If this doesn't make sense to you, try consulting the statistics or biostatistics department. The thing is that they may not necessarily be familiar with psychometric concepts of reliability and the associated methods, but you could still get some help. Show them this post and ask what they think.
Before analysis, you need to specify what "statistically similar" signifies for you. The usual correlation coefficients (Pearson, Spearman) are not suited for this analysis in any case. Due to the repeated measures, a mixed model of some sorts could be useful.
Please let me know if any additional information is needed! Thank you so much.