Straube E R, von Eye A, Müller M J
Universität Jena, Germany.
Pharmacopsychiatry. 1998 May;31(3):83-8. doi: 10.1055/s-2007-979306.
This article proposes a new nonparametric method for statistical evaluation of clinical pre-post treatment designs. In clinical research, models of marginal symmetry typically are estimated from log-linear models of axial and quasi-symmetry. As such, they provide overall goodness-of-fit information concerning change in probabilities of categories of one variable that was observed twice. This paper proposes the following three extensions: (1) using models of marginal symmetry for changes in patterns of two or more variables, and (2) following up global marginal symmetry tests using Lehmacher's sign tests. (3) To protect the experiment-wise alpha, a modified Bonferroni-Holm procedure is proposed. The new approach allows researchers to make statements about treatment effects at the level of single symptoms. Examples illustrate application of all three symmetry models and the follow-up test using data from pharmaco-psychiatry. The discussion relates Lehmacher's tests to two-sample Configural Frequency Analysis of multi-discrimination types. Strategies of statistical significance testing are presented and the importance of the proposed methodological approach for psychiatric research is discussed.
本文提出了一种用于临床治疗前后设计统计评估的新非参数方法。在临床研究中，边际对称模型通常从轴向和准对称的对数线性模型中估计得出。因此，它们提供了关于一个变量的类别概率变化的总体拟合优度信息，该变量被观测了两次。本文提出了以下三个扩展：（1）将边际对称模型用于两个或更多变量模式的变化；（2）使用莱马赫符号检验对全局边际对称检验进行后续分析；（3）为保护实验性α水平，提出了一种修正的邦费罗尼 - 霍尔姆程序。新方法允许研究人员在单个症状层面上对治疗效果进行陈述。实例说明了所有三种对称模型的应用以及使用药物精神病学数据进行的后续检验。讨论将莱马赫检验与多判别类型的两样本构型频率分析联系起来。介绍了统计显著性检验策略，并讨论了所提出的方法学方法对精神病学研究的重要性。
