Most neuroimaging studies are affected by small sample sizes and poor reproducibility of research findings. Therefore, aggregating data from multiple research centres is crucial to the development...Show moreMost neuroimaging studies are affected by small sample sizes and poor reproducibility of research findings. Therefore, aggregating data from multiple research centres is crucial to the development of the neuroimaging field. For this reason, MRI site harmonization is essential, as it allows for comparison and joint analysis of MRI data from multiple studies. MRI site harmonization aims to remove inter-site variability, while maintaining variance of interest. However, neuroimaging studies generally have low numbers of subjects to estimate the harmonization model. This paper examines the effect of dataset size on the quality of MRI site harmonization, and whether this effect is dependent on age differences between sites and the size of site differences. In order to evaluate the quality of MRI site harmonization we calculated the extent to which the correlation between GMD and age was recovered. To answer our research questions, we studied the performance of MRI site harmonization using a variety of training dataset sizes in an empirical study. Our empirical study shows no clear effect of the size of the training dataset. In addition, we studied the performance of MRI site harmonization in a simulation study, where we varied the number of subjects in the training dataset, the age differences between the centres, and the size of the centre effects. Our simulation study shows that the effect of training dataset size is minimal. The effect is only present when sites differ largely in mean age and when site effects are small. Thus, in all other conditions, inter-site variability is successfully removed, while variance of interest is preserved. This leads us to the conclusion that the limited effect of training dataset size suggests that prospects for the quality of harmonization in multi-centre studies with small datasets are promising.Show less