Warwick Medical School, The University of Warwick, Coventry, CV4 7AL, UK.
Stat Med. 2013 Aug 15;32(18):3181-91. doi: 10.1002/sim.5756. Epub 2013 Feb 11.
In many medical studies, researchers widely use composite or long ordinal scores, that is, scores that have a large number of categories and a natural ordering often resulting from the sum of a number of short ordinal scores, to assess function or quality of life. Typically, we analyse these using unjustified assumptions of normality for the outcome measure, which are unlikely to be even approximately true. Scores of this type are better analysed using methods reserved for more conventional (short) ordinal scores, such as the proportional-odds model. We can avoid the need for a large number of cut-point parameters that define the divisions between the score categories for long ordinal scores in the proportional-odds model by the inclusion of orthogonal polynomial contrasts. We introduce the repeated measures proportional-odds logistic regression model and describe for long ordinal outcomes modifications to the generalized estimating equation methodology used for parameter estimation. We introduce data from a trial assessing two surgical interventions, briefly describe and re-analyse these using the new model and compare inferences from the new analysis with previously published results for the primary outcome measure (hip function at 12 months postoperatively). We use a simulation study to illustrate how this model also has more general application for conventional short ordinal scores, to select amongst competing models of varying complexity for the cut-point parameters.
在许多医学研究中，研究人员广泛使用复合或长序评分，即具有大量类别且通常由许多短序评分之和得出的自然排序的评分，以评估功能或生活质量。通常，我们使用对结果测量不合理的正态性假设来分析这些结果，而这些假设不太可能接近真实情况。这种类型的分数最好使用为更传统（短）序评分保留的方法进行分析，例如比例优势模型。我们可以通过包含正交多项式对比来避免为长序评分的比例优势模型中定义分数类别的大量切点参数的需要。我们引入了重复测量比例优势逻辑回归模型，并描述了用于参数估计的广义估计方程方法的长序结果的修改。我们介绍了评估两种手术干预措施的试验数据，简要描述并使用新模型重新分析这些数据，并将新分析的推论与主要结果测量（术后 12 个月的髋关节功能）的先前发表结果进行比较。我们使用模拟研究来说明如何将此模型也更一般地应用于常规短序评分，以在不同复杂程度的竞争模型之间选择切点参数。
