Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Int J Methods Psychiatr Res. 2010 Jun;19(2):63-73. doi: 10.1002/mpr.301.
A primary challenge in psychiatric genetics is the lack of a completely validated system of classification for mental disorders. Appropriate statistical methods are needed to empirically derive more homogenous disorder subtypes.
Using the framework of Robins and Guze's ('Establishment of diagnostic validity in psychiatric illness: its application to schizophrenia', American Journal of Psychiatry, 1970, 126(7), 983-987) five phases, latent variable models to derive and validate diagnostic groups are described. A process of iterative validation is proposed through which refined phenotypes would facilitate research on genetics, pathogenesis, and treatment, which would in turn aid further refinement of disorder definitions.
Latent variable methods are useful tools for defining and validating psychiatric phenotypes. Further methodological research should address sample size issues and application to iterative validation.
精神疾病遗传学的一个主要挑战是缺乏对精神障碍进行完全验证的分类系统。需要适当的统计方法从经验上得出更同质的疾病亚型。
本文使用 Robins 和 Guze 的（“精神病诊断有效性的确立：其在精神分裂症中的应用”，美国精神病学杂志，1970 年，126（7），983-987）五个阶段的框架，描述了用于推导和验证诊断组的潜在变量模型。提出了一个迭代验证的过程，通过这个过程，精细的表型将有助于遗传学、发病机制和治疗的研究，反过来也将有助于进一步完善疾病定义。
潜在变量方法是定义和验证精神疾病表型的有用工具。进一步的方法学研究应解决样本量问题，并应用于迭代验证。
