I am currently working on the analysis of a metric comparing two methods (A & B) for subjective annotation. The two methods give 2 types of data which after processing gives scores relatives to the subjective dimension studied for a dataset of item.

In order to compare their performance, I do a reliability test called Split Half Reliability(SHR) that splits the dataset of each method's results in two subsets and compute a correlation coefficient between them. The highest correlation coefficient between two subsets means high reliability. However, there is a lot of variance depending on the organization of the data in each subsets, doing one SHR is therefore not accurate.

So I want to do a bootstrap procedure for each of the method with these steps:

For the two methods'results simultaneously : 1/ sample with replacement the participants data 2/ compute scores for the whole dataset 3/ compute SHR (correlation coefficient, for each method's dataset) 4/ redo steps 1-3 N times

At the end, I'm thinking of a T-test if the distributions of the two methods are normal.

I'm just not sure I'm allowed to follow these steps...

I would gladly take advice (and references if possible).

Thank you :)


1 Answer 1


I don't think the split half reliability is the best approach here. The problem with SHR is, as you say, that you can get a different value according to how you split.

Coefficient (Cronbach's) alpha is the average of all the possible split half correlations (it's also a form of ICC). You can calculate the standard error and do a t-test, or you can use a bootstrap, to compare them.

  • $\begingroup$ Thank you for your answer ! The thing with cronbach's alpha (or krippendorff's alpha) here is that I don't have repeated trials in my dataset. It is due to the design of the method i'm using - i.e. best-worst scaling for many items - and the comparison I'm doing with a rating scale method. So the type of raw data is very different for the two methods, and i have no repeated trials in the whole dataset of best-worst scaling. So the only common metric for the two methods is SHR... $\endgroup$
    – Heralm
    Commented Jul 21, 2021 at 22:33
  • $\begingroup$ Not sure I understand what your data look like. How are you splitting the data? $\endgroup$ Commented Jul 22, 2021 at 16:26

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