Combining several ordinal measures in clinical studies
Combining several ordinal measures in clinical studies
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DOI：
10.1002/sim.1778
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发表时间：
2004-05-30
影响因子：
2
通讯作者：
Krueger, JG
中科院分区：
文献类型：
--
作者：
Wittkowski, KM;Lee, E;Krueger, JG
在医学研究中，很少有单一变量足以代表流行病学风险、基因组活动、不良事件或临床反应的所有相关方面。由于生物系统在本质上既不是线性的，也不是分层的，基于线性模型的传统多元统计方法的假设往往不能在理论上得到证明。通过经验验证来建立概念有效性不仅有问题，而且耗时。本文提出了使用u-统计量对多元有序数据进行评分，并提出了一族简单的非参数检验。该评分方法被证明适用于银屑病治疗中的临床反应谱评分，然后鉴定与这些谱最相关的基因组途径。版权所有（C）2004约翰威利父子有限公司。
In medical research, it is rare that a single variable is sufficient to represent all relevant aspects of epidemiological risk, genomic activity, adverse events, or clinical response. Since biological systems tend to be neither linear, nor hierarchical in nature, the assumptions of traditional multivariate statistical methods based on the linear model can often not be justified on theoretical grounds. Establishing concept validity through empirical validation is not only problematic, but also time consuming. This paper proposes the use of u-statistics for scoring multivariate ordinal data and a family of simple nonparametric tests for analysis. The scoring method is demonstrated to be applicable to scoring clinical response profiles in the treatment of psoriasis and then to identifying genomic pathways that best correlate with these profiles. Copyright (C) 2004 John Wiley Sons, Ltd.