明智选择刺激物：视觉科学和眼科评估中单因素一刺激原则的个体差异应用逐步教程

Given that data collection time in vision research and clinical assessment is limited, investigators and clinicians must select stimuli that maximize diagnostic information with minimum redundancy. This article proposes that analyzing individual differences—through factor analysis (FA), principal component analysis (PCA), and multidimensional scaling (MDS)—offers a principled approach. The covariance structure of individual variation reveals the minimum number of independent factors underlying a visual function, and therefore the minimum number of stimuli needed for efficient, non-redundant ch