I am doing a study to evaluate the effect of ossification ligament on thoracic vertebra.
The purpose was to explore whether the evoked potentials is different between compressed area and uncompressed area in thoracic vertebra for patients. We collect 6 patients and divide their thoracic vertebra for compressed area and uncompressed area by MRI, respectively.
Then we examine the evoked potential for the thoracic vertebra.
For each patient, we choose five sites to detect the evoked potentials in the compressed area, and five sites to detect the evoked potentials in the uncompressed area too.
Therefore, here's the form of my data (Table1).




How to analyze our data for comparing the difference between compressed area and uncompressed area in thoracic vertebra for patients?
Firstly, we calculated the average for compressed area (site1~site5) and the average for uncompressed area (site1~site5) for each patient, respectively.
So, we compared the average between two groups (compressed area vs. uncompressed area) by paired t tests. However, is it correct way?

Actually, I am confused by the question:
In the current study, we measured the evoked potential in 5 sites for compressed area, and 5 sites for uncompressed area for one patient, respectively.
Could we consider this data as repeated measurement data? The sites were considered as repeated measures factor?
If this is a repeated measures design，how to analyze it?
Repeated Measures Analysis of Variance (ANOVA)?

Moreover, if the data was considered as repeated measured data and we have data missing in the dataset, which method should we choose for the study?
Mixed linear model, Generalized estimating equation or Generalized linear mixed effects model？
For example (Table 2):