Identifying predictors of within-person variance in MRI-based brain volume estimates
Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imag