Hall W
National Drug and Alcohol Research Centre, University of New South Wales, Kensington.
Aust N Z J Psychiatry. 1989 Dec;23(4):503-11. doi: 10.3109/00048678909062618.
Multivariate statistical methods have been widely used in the analysis of the multiple symptom data which are routinely collected in psychiatric research on the classification of depressive illnesses. The most commonly used methods, those of factor analysis and discriminant function analysis, were introduced into research on the classification of depressive illness with unreasonably high expectations about what they could achieve. The failure to realize these expectations has produced scepticism in some quarters about the usefulness of multivariate methods in psychiatric research. When evaluated more circumspectly, multivariate statistical methods have made a contribution to our understanding of depressive illnesses, and they will continue to do so, if they are used with more reasonable expectations.
多变量统计方法已广泛应用于对多种症状数据的分析,这些数据是在抑郁症分类的精神病学研究中常规收集的。最常用的方法,即因子分析和判别函数分析,被引入到抑郁症分类研究中时,人们对它们所能取得的成果抱有过高的期望。这些期望未能实现,在某些方面引发了对多变量方法在精神病学研究中实用性的怀疑。当进行更审慎的评估时,多变量统计方法为我们理解抑郁症做出了贡献,并且如果以更合理的期望来使用它们,它们将继续做出贡献。