I am struggling with deciding how to analyze the following data. I am investigating a new method to estimate hearing thresholds using EEG. About twenty subjects participated in the study. Each of these subjects underwent three types of tests:
- TLA: this is the true hearing threshold
- TB: this is the traditional EEG measurement for hearing threshold estimation
- NB: this is the new EEG measurement for hearing threshold estimation
For each test, the threshold could be obtained for 0.5, 1, 2, and 4 kHz. However, due to time constraints, it was impossible to obtain the thresholds for all types of tests and all frequencies in each subject. Therefore, I randomly selected frequencies. Although I did not manage to test every combination, for the frequencies that were tested, I do have the thresholds for each test (TLA, TB, NB).
There are two research questions:
- For each frequency, is NB a good estimator for the TLA?
- For each frequency, is NB a better estimator for the TLA than the TB?
My questions is: can I do a repeated-measures ANOVA for each frequency separately? Or do I need to do a generalized linear mixed model? I have never done generalized linear mixed models and I am new to R, so it would be nice if someone could help me out.